Journal articles: 'Second system of Estimation'

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Gao, Chao, Guorong Zhao, Jianhua Lu, and Shuang Pan. "Decentralized state estimation for networked spatial-navigation systems with mixed time-delays and quantized complementary measurements: The moving horizon case." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 232, no. 11 (June 8, 2017): 2160–77. http://dx.doi.org/10.1177/0954410017712277.

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In this paper, the navigational state estimation problem is investigated for a class of networked spatial-navigation systems with quantization effects, mixed time-delays, and network-based observations (i.e. complementary measurements and regional estimations). A decentralized moving horizon estimation approach, featuring complementary reorganization and recursive procedure, is proposed to tackle this problem. First, through the proposed reorganized scheme, a random delayed system with complementary observations is reconstructed into an equivalent delay-free one without dimensional augment. Second, with this equivalent system, a robust moving horizon estimation scheme is presented as a uniform estimator for the navigational states. Third, for the demand of real-time estimate, the recursive form of decentralized moving horizon estimation approach is developed. Furthermore, a collective estimation is obtained through the weighted fusion of two parts, i.e. complementary measurements based estimation, and regional estimations directly from the neighbors. The convergence properties of the proposed estimator are also studied. The obtained stability condition implicitly establishes a relation between the upper bound of the estimation error and two parameters, i.e. quantization density and delay occur probability. Finally, an application example to networked unmanned aerial vehicles is presented and comparative simulations demonstrate the main features of the proposed method.

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Crassidis, J. L., and D. J. Mook. "Integrated Estimation/Identification Using Second-Order Dynamic Models." Journal of Vibration and Acoustics 119, no. 1 (January 1, 1997): 1–8. http://dx.doi.org/10.1115/1.2889682.

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An algorithm is presented which accurately identifies multi-input-multi-output systems characterized by vibrating structures. More specifically, an identification technique is integrated with an optimal estimator in order to develop an algorithm which is robust with respect to measurement and process noise. The unique functional form of the integrated approach utilizes systems described by second-order models. Therefore, theoretical mass, damping, and stiffness matrices, associated with lumped parameter models, are tailored with experimental time-domain data for system estimation and identification. This leads to an algorithm that is computationally efficient, producing realizations of complex multiple degree-of-freedom systems. The combined estimation/identification algorithm is used to identify the properties of an actual flexible truss from experimental data. Comparison of experimental frequency-domain data to the predicted model characteristics indicates that the integrated algorithm produces near-minimal realizations coupled with accurate modal properties.

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Hosoya, Yuzo, Yoshihiko Tsukuda, and Nobuhiko Terui. "Ancillarity and the Limited Information Maximum-Likelihood Estimation of a Structural Equation in a Simultaneous Equation System." Econometric Theory 5, no. 3 (December 1989): 385–404. http://dx.doi.org/10.1017/s0266466600012585.

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The concepts of the curved exponential family of distributions and ancillarity are applied to estimation problems of a single structural equation in a simultaneous equation model, and the effect of conditioning on ancillary statistics on the limited information maximum-likelihood (LIML) estimator is investigated. The asymptotic conditional covariance matrix of the LIML estimator conditioned on the second-order asymptotic maximal ancillary statistic is shown to be efficiently estimated by Liu and Breen's formula. The effect of conditioning on a second-order asymptotic ancillary statistic, i.e., the smallest characteristic root associated with the LIML estimation, is analyzed by means of an asymptotic expansion of the distribution as well as the exact distribution. The smallest root helps to give an intuitively appealing measure of precision of the LIML estimator.

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Mohamed, Majeed, and Indra Narayan Kar. "Stochastic contraction based online estimation of second order wiener system." ISA Transactions 69 (July 2017): 131–39. http://dx.doi.org/10.1016/j.isatra.2017.05.004.

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Izah, Rofiatul, Subiyanto Subiyanto, and Dhidik Prastiyanto. "Improvement of DSOGI PLL Synchronization Algorithm with Filter on Three-Phase Grid-connected Photovoltaic System." Jurnal Elektronika dan Telekomunikasi 18, no. 1 (August 31, 2018): 35. http://dx.doi.org/10.14203/jet.v18.35-45.

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Synchronous Reference Frame Phase Locked Loop (SRF PLL) has been widely used for synchronization three-phase grid-connected photovoltaic (PV) system. On the grid fault, SRF PLL distorted by negative sequence component and grid harmonic that caused an error in estimating parameter because of ripple and oscillation. This work combined SRF PLL with Dual Second Order Generalized Integrator (DSOGI) and filter to minimize ripple and minimize oscillation in the phase estimation and frequency estimation. DSOGI was used for filtering and obtaining the 90o shifted versions from the vαβ signals. These signals (vαβ) were generated from three phase grid voltage signal using Clarke transform. The vαβ signal was the inputs to the positive-sequence calculator (PSC). The positive-sequence vαβ was transformed to the dq synchronous reference frame and became an input to SRF-PLL to create the estimation frequency. This estimation frequency from SRF PLL was filtered by the low-pass filter to decrease grid harmonic. Moreover, the output of low-pass filter was a frequency adaptive. The performance of DSOGI PLL with filter is compared with DSOGI PLL, SRF PLL, and IEEE standard 1547(TM)-2003. The improvement of DSOGI PLL with filter gave better performances than DSOGI PLL and SRF PLLbecause it minimized ripples and oscillations in the phase and frequency estimations.

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Sun, Shaoxin, Huaguang Zhang, Jian Han, and Yuling Liang. "A novel double-level observer-based fault estimation for Takagi–Sugeno fuzzy systems with unknown nonlinear dynamics." Transactions of the Institute of Measurement and Control 41, no. 12 (February 5, 2019): 3372–84. http://dx.doi.org/10.1177/0142331219826655.

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In this paper we investigate the fault estimation problem against local unknown nonlinear dynamics, sensor and actuator faults for a class of Takagi–Sugeno (T-S) fuzzy systems. In addition, the exogenous disturbances and measurement noise are considered, which are presented in the operation of the systems and are various and independent of the systems. A novel double-level observer is designed to estimate the system states and faults. Compared with the current research results, the proposed observer has a wider range of application. By designing a fuzzy augmented system and a Kalman filter as the first-level observer, the estimations of system states, sensor faults and actuator faults can be obtained simultaneously. The second-level observer can estimate the unknown nonlinear dynamic function by establishing generalized fuzzy hyperbolic model. The robust stability of the estimation error systems is considered by H∞ performance. Finally, three simulation examples are provided to demonstrate the effectiveness of the proposed fault estimation method.

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Lin, Qizhe, Xiaoqi Li, Bicheng Tu, Junwei Cao, Ming Zhang, and Jiawei Xiang. "Stable and Accurate Estimation of SOC Using eXogenous Kalman Filter for Lithium-Ion Batteries." Sensors 23, no. 1 (January 1, 2023): 467. http://dx.doi.org/10.3390/s23010467.

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The state of charge (SOC) for a lithium-ion battery is a key index closely related to battery performance and safety with respect to the power supply system of electric vehicles. The Kalman filter (KF) or extended KF (EKF) is normally employed to estimate SOC in association with the relatively simple and fast second-order resistor-capacitor (RC) equivalent circuit model for SOC estimations. To improve the stability of SOC estimation, a two-stage method is developed by combining the second-order RC equivalent circuit model and the eXogenous Kalman filter (XKF) to estimate the SOC of a lithium-ion battery. First, approximate SOC estimation values are observed with relatively poor accuracy by a stable observer without considering parameter uncertainty. Second, the poor accuracy SOC results are further fed into XKF to obtain relative stable and accurate SOC estimation values. Experiments demonstrate that the SOC estimation results of the present method are superior to those of the commonly used EKF method. It is expected that the present two-stage XKF method will be useful for the stable and accurate estimation of SOC in the power supply system of electric vehicles.

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Ordaz, Patricio, Liliam Rodríguez-Guerrero, Omar Santos, Carlos Cuvas, Hugo Romero, Mario Ordaz-Oliver, and Pablo López-Pérez. "Parameter estimation of a second order system via nonlinear identification algorithm." IOP Conference Series: Materials Science and Engineering 844 (June 30, 2020): 012038. http://dx.doi.org/10.1088/1757-899x/844/1/012038.

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9

Huang, Chi Tsung, and Chin Jui Chou. "Estimation of the underdamped second-order parameters from the system transient." Industrial & Engineering Chemistry Research 33, no. 1 (January 1994): 174–76. http://dx.doi.org/10.1021/ie00025a024.

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Delpoux, Romain, Thierry Floquet, and Hebertt Sira-Ramírez. "Finite-Time Trajectory Tracking of Second-Order Systems Using Acceleration Feedback Only." Automation 2, no. 4 (December 16, 2021): 266–77. http://dx.doi.org/10.3390/automation2040017.

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In this paper, an algebraic approach for the finite-time feedback control problem is provided for second-order systems where only the second-order derivative of the controlled variable is measured. In practice, it means that the acceleration is the only variable that can be used for feedback purposes. This problem appears in many mechanical systems such as positioning systems and force-position controllers in robotic systems and aerospace applications. Based on an algebraic approach, an on-line algebraic estimator is developed in order to estimate in finite time the unmeasured position and velocity variables. The obtained expressions depend solely on iterated integrals of the measured acceleration output and of the control input. The approach is shown to be robust to noisy measurements and it has the advantage to provide on-line finite-time (or non-asymptotic) state estimations. Based on these estimations, a quasi-homogeneous second-order sliding mode tracking control law including estimated position error integrals is designed illustrating the possibilities of finite-time acceleration feedback via algebraic state estimation.

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Galtier, Thomas, Sayan Gupta, and Igor Rychlik. "Crossings of Second-Order Response Processes Subjected to LMA Loadings." Journal of Probability and Statistics 2010 (2010): 1–22. http://dx.doi.org/10.1155/2010/752452.

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The focus of this paper is on the estimation of the crossing intensities of responses for second-order dynamical systems, subjected to stationary, non-Gaussian external loadings. A new model for random loadings—the Laplace driven moving average (LMA)—is used. The model is non-Gaussian, strictly stationary, can model any spectrum, and has additional flexibility to model the skewness and kurtosis of the marginal distribution. The system response can be expressed as a second-order combination of the LMA processes. A numerical technique for estimating the level crossing intensities for such processes is developed. The proposed method is a hybrid method which combines the saddle-point approximation with limited Monte Carlo simulations. The performance and the accuracy of the proposed method are illustrated through a set of numerical examples.

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Chinsatit, Warapon, and Takeshi Saitoh. "CNN-Based Pupil Center Detection for Wearable Gaze Estimation System." Applied Computational Intelligence and Soft Computing 2017 (2017): 1–10. http://dx.doi.org/10.1155/2017/8718956.

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This paper presents a convolutional neural network- (CNN-) based pupil center detection method for a wearable gaze estimation system using infrared eye images. Potentially, the pupil center position of a user’s eye can be used in various applications, such as human-computer interaction, medical diagnosis, and psychological studies. However, users tend to blink frequently; thus, estimating gaze direction is difficult. The proposed method uses two CNN models. The first CNN model is used to classify the eye state and the second is used to estimate the pupil center position. The classification model filters images with closed eyes and terminates the gaze estimation process when the input image shows a closed eye. In addition, this paper presents a process to create an eye image dataset using a wearable camera. This dataset, which was used to evaluate the proposed method, has approximately 20,000 images and a wide variation of eye states. We evaluated the proposed method from various perspectives. The result shows that the proposed method obtained good accuracy and has the potential for application in wearable device-based gaze estimation.

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Rodríguez-Abreo, Omar, Juvenal Rodríguez-Reséndiz, Francisco Antonio Castillo Velásquez, Alondra Anahi Ortiz Verdin, Juan Manuel Garcia-Guendulain, and Mariano Garduño-Aparicio. "Estimation of Transfer Function Coefficients for Second-Order Systems via Metaheuristic Algorithms." Sensors 21, no. 13 (July 1, 2021): 4529. http://dx.doi.org/10.3390/s21134529.

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The present research develops the parametric estimation of a second-order transfer function in its standard form, employing metaheuristic algorithms. For the estimation, the step response with a known amplitude is used. The main contribution of this research is a general method for obtaining a second-order transfer function for any order stable systems via metaheuristic algorithms. Additionally, the Final Value Theorem is used as a restriction to improve the velocity search. The tests show three advantages in using the method proposed in this work concerning similar research and the exact estimation method. The first advantage is that using the Final Value Theorem accelerates the convergence of the metaheuristic algorithms, reducing the error by up to 10 times in the first iterations. The second advantage is that, unlike the analytical method, it is unnecessary to estimate the type of damping that the system has. Finally, the proposed method is adapted to systems of different orders, managing to calculate second-order transfer functions equivalent to higher and lower orders. Response signals to the step of systems of an electrical, mechanical and electromechanical nature were used. In addition, tests were carried out with simulated signals and real signals to observe the behavior of the proposed method. In all cases, transfer functions were obtained to estimate the behavior of the system in a precise way before changes in the input. In all tests, it was shown that the use of the Final Value Theorem presents advantages compared to the use of algorithms without restrictions. Finally, it was revealed that the Gray Wolf Algorithm has a better performance for parametric estimation compared to the Jaya algorithm with an error up to 50% lower.

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Allaw, Kamel, Jocelyne Adjizian Gerard, Makram Zouheir Chehayeb, and Nada Badaro Saliba. "Population estimation using geographic information system and remote sensing for unorganized areas." Geoplanning: Journal of Geomatics and Planning 7, no. 2 (January 1, 2021): 75–86. http://dx.doi.org/10.14710/geoplanning.7.2.75-86.

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Population estimation using remotely sensed data has been largely discussed in the literature relative to human geography. However, the previously established models can be applied on organized areas (mainly urban areas) but they are not suitable for unorganized areas which already suffer from a lack of population data. So, the aim of this study is the establish a statistical model for population estimation based on remote sensing data and suitable for unorganized areas. To do so, the morphological characteristics have been studied and a bivariate analysis was carried out to determine factors having a strong relationship with population data as a first step. Second, factors with strongest correlations have been chosen to establish the required model. As a result, an equation has been generated which relates the population data to building volume, density of roads, number of nodes, actual urban areas, and urban trend.

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Cai, Xin. "High Accuracy Simulation for the Weakly Coupled System of Two Second Order Ordinary Differential Equations." Key Engineering Materials 467-469 (February 2011): 377–82. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.377.

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Coupled system of two second order ordinary differential equations with small parameter was considered. This is a multi-scale system. The solution of the system will change rapidly near both sides of the boundary layer. The system was decomposed into several systems in order to have fourth order asymptotic decomposition firstly. The asymptotic properties of all these systems were discussed secondly. The third order numerical methods were constructed for left side and right side singular component systems thirdly. The error estimation for the system was given finally.

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Aljabrine, Abdulwahab A., Abdallah A. Smadi, Yacine Chakhchoukh, Brian K. Johnson, and Hangtian Lei. "Resiliency Improvement of an AC/DC Power Grid with Embedded LCC-HVDC Using Robust Power System State Estimation." Energies 14, no. 23 (November 23, 2021): 7847. http://dx.doi.org/10.3390/en14237847.

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The growth of renewable energy generation in the power grid brings attention to high-voltage direct current (HVDC) transmission as a valuable solution for stabilizing the system. Robust hybrid power system state estimation could enhance the resilience of the control of these systems. This paper proposes a two-stage, highly robust least-trimmed squares (LTS)-based estimator. The first step combines the supervisory control and data acquisition (SCADA) measurements using the robust LTS-based estimator. The second step merges the obtained state results with the available phasor measurement units (PMUs) measurements using a robust Huber M-estimator. The proposed robust LTS-based estimator shows good performance in the presence of Gaussian measurement noise. The proposed estimator is shown to resist and correct the effect of false data injection (FDI) attacks and random errors on the measurement vector and the Jacobian matrix. The state estimation (SE) is executed on a modified version of the CIGRE bipole LCC-HVDC benchmark model integrated into the IEEE 12-bus AC dynamic test system. The obtained simulation results confirm the effectiveness and robustness of the proposed two-stage LTS-based SE.

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Volosnikov, Andrei S. "Adaptive measuring system with dynamic error estimation of the second-order sensor." Measurement: Sensors 18 (December 2021): 100142. http://dx.doi.org/10.1016/j.measen.2021.100142.

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Micheletti, R. "Dynamic parameter estimation of a second-order system to a step function." IEEE Transactions on Instrumentation and Measurement 39, no. 5 (1990): 790–92. http://dx.doi.org/10.1109/19.58627.

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He, Xianwen, Gaoqi Dou, and Jun Gao. "Channel Estimation for OFDM-Based Amplify-and-Forward Cooperative System Using Relay-Superimposed Pilots." International Journal of Digital Multimedia Broadcasting 2018 (2018): 1–6. http://dx.doi.org/10.1155/2018/9618147.

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For the OFDM-based Amplify-and-Forward cooperative system, a novel relay-superimposed pilot strategy is proposed, where the source pilot symbols are frequency division multiplexed to estimate the cascaded channel while relay pilot sequence is superimposed onto the top of the cooperative data stream for second-hop channel estimation. This method avoids the loss of data rate for additional pilot subcarriers but results in the interference of unknown cooperative data. To remove the interference of cooperative data during the estimation of second-hop channel, the Cooperative Interference Cancelation scheme assisted by cooperative data from direct link is proposed. We derive the approximated lower bound for the MSE of second-hop channel estimation. Simulation results are presented to validate the performance of the proposed schemes.

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Ganesh, Sai Vinayak, and Matilde D’Arpino. "Critical Comparison of Li-Ion Aging Models for Second Life Battery Applications." Energies 16, no. 7 (March 26, 2023): 3023. http://dx.doi.org/10.3390/en16073023.

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Lithium-ion batteries (LIBs) from electrified vehicles (EVs) that have reached the automotive end of life (EoL) may provide a low-cost, highly available energy storage solution for grid-connected systems, such as peak shaving and ancillary services. There are several issues related to the integration of second life batteries (SLBs) in power systems, such as the variability of the pack design and cell chemistry, in-field assessments of the state of health (SoH), and estimations of the expected lifetimes of SLBs in different power system applications. Model-based approaches are commonly used in the automotive industry for estimating/predicting the capacity and power fade trajectories of LIBs during their life. However, a large variety of models are available with different fidelities, complexities, and computational costs. The accuracy of these estimations is critical for the derivation of business models for SLB applications. This paper presents a qualitative and quantitative assessment of the performance of two well-accepted, state-of-the-art aging models, initially developed for automotive applications and here applied to different SLB applications to predict both the capacity and power fade. These models are evaluated with respect to several performance metrics, such as fidelity of estimation and capability of extrapolation outside the calibration data range. The considered models are classified as semi-empirical physics-based and empirical models, respectively. Three different SLB power profiles, bulk energy for DC fast charge stations and two frequency regulation profiles, are considered, corresponding to different ranges of the SoC, C-rates, and battery temperatures, with the aim of exciting different aging mechanisms. The numerical results provide insight for the selection of aging models for SLB applications based on their performances and limitations.

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Thi Nga, Nguyen, Huy Anh Phan, Van Loi Cao, and Thanh Hiep Pham. "Suitable pilot search method for channel estimation in underwater acoustic OFDM systems." Journal of Military Science and Technology 89 (August 25, 2023): 52–59. http://dx.doi.org/10.54939/1859-1043.j.mst.89.2023.52-59.

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The underwater environment poses challenges to the Underwater Acoustic OFDM (UWA-OFDM) system, causing the tendency of lacking pilots to recover the channel impulse response (CIR). Our previous research (pilot enrichment estimator) supplemented potential pilots based on the distance to the nearest constellation point below a fixed threshold T. However, this does not guarantee that the extracted pilots have sufficiently good quality. Therefore, this article presents a suitable pilot search (SPS) method with the flexible threshold T and second minimum mean square error (MMSE) estimation to improve channel estimation effectiveness in UWA-OFDM systems. Our approach is compared to the MMSE and PE methods across various criteria, such as pilot spacing and different modulators. The experiments demonstrate that the SPS estimator performs better than the MMSE and PE techniques regarding bit error rate (BER).

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Matevosyan, Ashot A., and Aram G. Matevosyan. "PARAMETER ESTIMATION FOR OSCILLATORY SYSTEMS." Proceedings of the YSU A: Physical and Mathematical Sciences 55, no. 2 (255) (August 30, 2021): 131–40. http://dx.doi.org/10.46991/pysu:a/2021.55.2.131.

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Simple harmonic motion was investigated of a rotational oscillating system. The effect of dumping and forcing on motion of the system was examined and measurements were taken. Resonance in a oscillating system was investigated and quality factor of the dumping system was measured at different damping forces using three different methods. Resonance curves were constructed at two different damping forces. A probabilistic model was built and system parameters were estimated from the resonance curves using Stan sampling platform. The quality factor of the oscillating system when the additional dumping was turned off was estimated to be $Q = \num{71 \pm 1}$ and natural frequency $\omega_0 = \num{3.105 \pm 0.008}\, \si{\per\second}$.

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Wakamatsu, Kazue, and Masashi Matsuoka. "Nationwide 7.5-Arc-Second Japan Engineering Geomorphologic Classification Map and Vs30 Zoning." Journal of Disaster Research 8, no. 5 (October 1, 2013): 904–11. http://dx.doi.org/10.20965/jdr.2013.p0904.

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Local geological and ground conditions play important roles in characterizing and estimating hazards in seismic hazard assessment. The authors recently constructed the Japan Engineering Geomorphologic Classification Map (JEGM), which is a systematically standardized GIS-based ground-condition map containing attributes of geomorphologic classification in grid cells of 7.5 arc-seconds in latitude × 11.25 arc-seconds in longitude for Japan nationwide. This paper introduces the concept of developing the 7.5-arc-second JEGM, and presents sample JEGM images. As an example of the database’s application in estimating hazards, the average shear velocity of the ground in the upper 30m, Vs30 is estimated and mapped for Japan nationwide. Other applications being released include seismic hazard maps of Japan, seismic risk analysis by Central Disaster Prevention Council and local governments, and a Quick Estimation System for Earthquake Maps Triggered by Observation Records (QuiQuake).

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Xie, Lin Bo, Fang Huang, and He Guang Liu. "State Estimation and Stability Analysis of Networked Control Systems with Multi-Quantized Output Feedback." Applied Mechanics and Materials 48-49 (February 2011): 1101–5. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.1101.

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This paper is concerned with closed-loop stability analysis and dynamic quantization parameters design of discrete-time networked control systems (NCSs) with noise disturbance. First, based on the Lyapunov function, two state invariant regions of estimation error system and plant system are constructed. The quadratically attractive conditions of the two systems are obtained by using the proposed invariant region sequence, respectively. Second, a quantized control strategy is presented by dynamically adjusting the scaling parameters of logarithmic quantizers. Moreover, the connection of quadratic stability between the plant system and the estimation error system is also given.

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Guo, Jianguo, Yuchao Liu, and Jun Zhou. "New adaptive sliding mode control for a mismatched second-order system using an extended disturbance observer." Transactions of the Institute of Measurement and Control 41, no. 1 (April 19, 2018): 276–84. http://dx.doi.org/10.1177/0142331218761560.

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An adaptive sliding mode control (ASMC) approach for a second-order system based on an extended disturbance observer (EDO) is proposed in this paper for systems with mismatched uncertainties. The EDO-based ASMC method is investigated to eliminate the effect of mismatched disturbance by using a novel adaptive sliding surface consisting of the disturbance estimation. The proposed method exhibits the following two attractive features: Firstly, the proposed adaptive sliding mode with disturbance estimation is insensitive to the mismatched disturbance; that is, the asymptotical stability of the adaptive sliding mode can be guaranteed in the presence of the disturbance estimation error of the EDO. Secondly, the chattering in traditional sliding mode control methods is eliminated by using an adaptive term the adaptive parameter. Compared with the disturbance-observer-based sliding mode control and the EDO-based modified sliding mode control method, numerical simulation results and application examples show that the proposed approach is robust, has the best dynamic performance and eliminates chattering.

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Kochneva, Daria, Vasily Say, and Valentina Parshina. "Estimation of container system development in a region." MATEC Web of Conferences 216 (2018): 02022. http://dx.doi.org/10.1051/matecconf/201821602022.

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A relevant problem of scientific research is formalization of the processes of interaction between transportation systems and the region in the context of modern ideas of synergetic approach. The purpose of this article is to develop a methodology for assessing and forecasting the needs of a region for container transport system development. The methodology includes two elements. First is the model for forecasting region's demand for container transportation based on the methods of correlation-regression analysis, index prediction and the Monte Carlo method. Second is the imitation model for assessing the needs of the region in the technical and organizational development of the container system. Organizational development is achieved due to system integration of market players, coordinated management of container flows, which makes it possible to establish the synergistic effect availability.

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Liu, Mengzhuo, Jifeng Zhu, Xiaohe Pan, Guolin Wang, Jun Liu, Zheng Peng, and Jun-Hong Cui. "A Distributed Intelligent Buoy System for Tracking Underwater Vehicles." Journal of Marine Science and Engineering 11, no. 9 (August 24, 2023): 1661. http://dx.doi.org/10.3390/jmse11091661.

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Underwater vehicles play a crucial role in various underwater applications, such as data collection in underwater sensor networks, target detection and tracking, and underwater pipeline monitoring. Real-time acquisition of their states, particularly their location and velocity, is vital for their operation and navigation. Consequently, the development of a remote tracking system to monitor these states is essential. In this paper, we propose a system that can track the underwater vehicle’s location and velocity. We take a systematic approach that encompasses the system architecture, system composition, signal processing, and mobility state estimation. We present the system architecture and define its components, along with their relationships and interfaces. The beacon signal employed in the system features dual-hyperbolic-frequency-modulated (HFM) waveform and an OFDM symbol with cyclic prefix (CP). Based on this beacon signal, we demonstrate how signal processing techniques are utilized to precisely determine the time of arrival and reduce false alarm rates in underwater acoustic channels affected by impulsive noise. Additionally, we explain how the CP-OFDM symbol is used to measure the Doppler scaling factor and transmit essential information for localization and velocity estimation purposes. Utilizing the measurements obtained through signal processing, least squares estimators are used for estimating both the location and velocity. To validate the effectiveness of our approach, we implement the system and conduct field trials. Two separate experiments were conducted in which the diagonal lengths of the square topology were designed to be 1000 m and 800 m. The minimum/maximum root mean square error of localization in the first and second experiment is 2.36/2.91 m and 1.47/2.49 m, respectively. And the minimum/maximum root mean square error of velocity estimation in the first and second experiment is 0.16/0.47 m/s and 0.21/0.76 m/s, respectively. Results confirm the effectiveness of the proposed method in estimating the location and velocity of the underwater vehicle. Overall, this paper provides a practical and effective design of a system to track the location and velocity of underwater vehicles. By leveraging the proposed system, signal processing, and mobility state estimation methods, our work offers a systematic solution. And, the successful field experiment serves as evidence of the feasibility and effectiveness of the proposed system, making it a valuable contribution to the field of tracking underwater vehicles.

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Tereshkov, Vasiliy M. "An Intuitive Approach to Inertial Sensor Bias Estimation." International Journal of Navigation and Observation 2013 (July 2, 2013): 1–6. http://dx.doi.org/10.1155/2013/762758.

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A simple approach to gyro and accelerometer bias estimation is proposed. It does not involve Kalman filtering or similar formal techniques. Instead, it is based on physical intuition and exploits a duality between gimbaled and strapdown inertial systems. The estimation problem is decoupled into two separate stages. At the first stage, inertial system attitude errors are corrected by means of a feedback from an external aid. In the presence of uncompensated biases, the steady-state feedback rebalances those biases and can be used to estimate them. At the second stage, the desired bias estimates are expressed in a closed form in terms of the feedback signal. The estimator has only three tunable parameters and is easy to implement and use. The tests proved the feasibility of the proposed approach for the estimation of low-cost MEMS inertial sensor biases on a moving land vehicle.

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Li, Shusheng, Yongling Fu, and Ping Liu. "Position Estimation and Compensation Based on a Two-Step Extended Sliding-Mode Observer for a MSFESS." Sensors 18, no. 8 (July 30, 2018): 2467. http://dx.doi.org/10.3390/s18082467.

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This paper aims to deal with the problem of rotor position estimation and compensation for a magnetically suspended flywheel energy storage system under the consideration of measurement noise and unknown disturbances. First, the flywheel system working principle and description are analyzed and, based on this, the mathematical model as well as the coordinates transformation are introduced. For the purpose of the state estimation, a two-step extended sliding-mode observer is considered to obtain the estimates of the rotor angular position. In this control strategy, a traditional sliding-mode observer is adopted as a first-step original state estimator. After that, the relationship between the angular position and the estimation error is established and a second-step observer is designed to obtain the estimation of the error. The estimated error is then used to compensate the real values of the rotor angular position generated by the first-step observer. To reject the influences of the measurement noise and unknown disturbances, the H∞ optimization strategy is considered to determine the second-step observer structure. Finally, experimental results are presented to demonstrate the effectiveness of the proposed method. It is demonstrated that the proposed two-step observer method has a better estimation accuracy and control performance.

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Véliz-Tejo, Adolfo, Juan Carlos Travieso-Torres, Andrés A. Peters, Andrés Mora, and Felipe Leiva-Silva. "Normalized-Model Reference System for Parameter Estimation of Induction Motors." Energies 15, no. 13 (June 21, 2022): 4542. http://dx.doi.org/10.3390/en15134542.

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This manuscript proposes a short tuning march algorithm to estimate induction motors (IM) electrical and mechanical parameters. It has two main novel proposals. First, it starts by presenting a normalized-model reference adaptive system (N-MRAS) that extends a recently proposed normalized model reference adaptive controller for parameter estimation of higher-order nonlinear systems, adding filtering. Second, it proposes persistent exciting (PE) rules for the input amplitude. This N-MRAS normalizes the information vector and identification adaptive law gains for a more straightforward tuning method, avoiding trial and error. Later, two N-MRAS designs consider estimating IM electrical and mechanical parameters. Finally, the proposed algorithm considers starting with a V/f speed control strategy, applying a persistently exciting voltage and frequency, and applying the two designed N-MRAS. Test bench experiments validate the efficacy of the proposed algorithm for a 10 HP IM.

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Ananyev, Boris. "About control of guaranteed estimation." Cybernetics and Physics, Volume 7, 2018, Number 1 (June 18, 2018): 18–25. http://dx.doi.org/10.35470/2226-4116-2018-7-1-18-25.

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The control problem by parameters in the course of the guaranteed state estimation of linear non-stationary systems is considered. It is supposed that unknown disturbances in the system and the observation channel are limited by norm in the space of square integrable functions and the initial state of the system is also unknown. The process of guaranteed state estimation includes the solution of a matrix Riccati equation that contains some parameters, which may be chosen at any instant of time by the first player (an observer) and the second player (an opponent of the observer). The purposes of players are diametrically opposite: the observer aims to minimize diameter of information set at the end of observation process, and the second player on the contrary aims to maximize it. This problem is interpreted as a differential game with two players for the Riccati equation. All the choosing parameters are limited to compact sets in appropriate spaces of matrices. The payoff of the game is interpreted through the Euclidean norm of the inverse Riccati matrix at the end of the process. A specific case of the problem with constant matrices is considered. Methods of minimax optimization, the theory of optimal control, and the theory of differential games are used. Examples are also given.

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Berger, Guillaume O., and Raphael M. Jungers. "Worst-case topological entropy and minimal data rate for state estimation of switched linear systems." Communications of the ACM 65, no. 2 (February 2022): 111–18. http://dx.doi.org/10.1145/3505269.

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In this paper, we study the problem of estimating the state of a switched linear system (SLS), when the observation of the system is subject to communication constraints. We introduce the concept of worst-case topological entropy of such systems, and we show that this quantity is equal to the minimal data rate (number of bits per second) required for the state estimation of the system under arbitrary switching. Furthermore, we provide a closed-form expression for the worst-case topological entropy of switched linear systems, showing that its evaluation reduces to the computation of the joint spectral radius (JSR) of some lifted switched linear system obtained from the original one by using tools from multilinear algebra, and thus can benefit from well-established algorithms for the stability analysis of switched linear systems. Finally, drawing on this expression, we describe a practical coder-decoder that estimates the state of the system and operates at a data rate arbitrarily close to the worst-case topological entropy.

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Parker, Danny L., William G. Frazier, and Mathew A. Gray. "Damage Localization Using Levenberg-Marquardt Optimization." Key Engineering Materials 347 (September 2007): 95–100. http://dx.doi.org/10.4028/www.scientific.net/kem.347.95.

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In this paper, an optimal solution method is proposed for determining the location of change, i.e. damage, within a perturbed system utilizing a nonlinear pseudo-second order search algorithm based on function evaluations and gradient information. This method is applied to damped vibrating systems and utilizes stiffness matrix sensitivities to determine the direction of search within the estimation. The site of damage (location of change) is the solution which minimizes the error between the predicted and measured change. A by-product of the Levenberg- Marquardt algorithm is an estimation of the magnitude of the change within the system which correlates to damage extent. A second-order model of a dynamic system is used, and an approximation is developed to describe small perturbations within the system.

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Xu, Dezhi, Bin Jiang, and Peng Shi. "Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy model." International Journal of Applied Mathematics and Computer Science 22, no. 1 (March 1, 2012): 183–96. http://dx.doi.org/10.2478/v10006-012-0014-9.

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Nonlinear actuator fault estimation observer: An inverse system approach via a T-S fuzzy modelBased on a Takagi-Sugeno (T-S) fuzzy model and an inverse system method, this paper deals with the problem of actuator fault estimation for a class of nonlinear dynamic systems. Two different estimation strategies are developed. Firstly, T-S fuzzy models are used to describe nonlinear dynamic systems with an actuator fault. Then, a robust sliding mode observer is designed based on a T-S fuzzy model, and an inverse system method is used to estimate the actuator fault. Next, the second fault estimation strategy is developed. Compared with some existing techniques, such as adaptive and sliding mode methods, the one presented in this paper is easier to be implemented in practice. Finally, two numerical examples are given to demonstrate the efficiency of the proposed techniques.

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Filasová, Anna, Dušan Krokavec, and Vladimír Serbák. "Application of descriptor approaches in design of PD observer-based actuator fault estimation." Archives of Control Sciences 25, no. 1 (March 1, 2015): 51–64. http://dx.doi.org/10.1515/acsc-2015-0004.

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Abstract Stability analysis and design for continuous-time proportional plus derivative state observers is presented in the paper with the goal to establish the system state and actuator fault estimation. Design problem accounts a descriptor principle formulation for non-descriptor systems, guaranteing asymptotic convergence both the state observer error as fault estimate error. Presented in the sense of the second Lyapunov method, an associated structure of linear matrix inequalities is outlined to possess parameter existence of the proposed estimator structure. The obtained design conditions are verified by simulation using a numerical illustrative example.

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Shams, Zahra, and Aref Shahmansoorian. "Fault estimation based on observer for chaotic Lorenz system with bifurcation problem." Transactions of the Institute of Measurement and Control 42, no. 3 (October 20, 2019): 576–85. http://dx.doi.org/10.1177/0142331219879267.

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In this paper, the simultaneous estimation of the process and sensor fault of a chaotic Lorenz system in a noisy environment is investigated. The problem of the process fault leads to the occurrence of a bifurcation in the Lorenz system. The purpose of this article is to combine the concept of fault and bifurcation. Fault diagnosis of nonlinear systems becomes more practicable when it is managed over Takagi-Sugeno (TS) approximated fuzzy models. TS fuzzy model unknown input observer can estimate faults and states. In this respect, a TS fuzzy model augmented by a proportional plus integral, for fault modeling observer (FO) is lined up for the estimation of the unmeasured signal. The simulation conclusions hint that the observer runs well in estimating process fault, states, and sensor fault. Using these estimates, the deviation value of a parameter is determined from its actual value, which is the same as the low amount of deviation in this article because the bifurcation occurs in the system. In the first part of the simulation, the process fault occurs and drives system behavior into chaos, and the bifurcation diagram uses to explain it. In the second part, the system is influenced by actuator fault. The conclusion is validated through extensive simulations.

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Kumar, Prashant, Sarvesh Sonkar, Ajoy Kanti Ghosh, and Deepu Philip. "Sensor Based System Identification in Real Time for Noise Covariance Deficient Models." Defence Science Journal 72, no. 5 (November 1, 2022): 665–78. http://dx.doi.org/10.14429/dsj.72.17663.

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System identification methods have extensive application in the aerospace industry’s experimental stability and control studies. Accurate aerodynamic modeling and system identification are necessary because they enable performance evaluation, flight simulation, control system design, fault detection, and model aircraft’s complex non-linear behavior. Various estimation methods yield different levels of accuracies with varying complexity and computational time requirements. The primary motivation of such studies is the accurate quantification of process noise. This research evaluates the performance of two recursive parameter estimation methods, viz.; First is the Fourier Transform Regression (FTR). The second approach describes the Extended version of Recursive Least Square (EFRLS), where E.F. refers to the Extended Forgetting factor. Also, the computational viability of these methods was analyzed for real-time application in aerodynamic parameter estimation for both linear and non-linear systems. While the first method utilizes the frequency domain to evaluate aerodynamic parameters, the second method works when noise covariances are unknown. The performance of both methods was assessed by benchmarking against parameter estimates from established methods like Extended Kalman Filter (EKF), Unscented Kalman Filter (UNKF), and Output Error Method (OEM).

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Sarkar, Arghya, and Samarjit Sengupta. "Bandpass Second-Degree Digital-Integrator-Based Power System Frequency Estimation Under Nonsinusoidal Conditions." IEEE Transactions on Instrumentation and Measurement 60, no. 3 (March 2011): 846–53. http://dx.doi.org/10.1109/tim.2009.2036467.

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Sarkar, A., and S. Sengupta. "Second-degree digital differentiator-based power system frequency estimation under non-sinusoidal conditions." IET Science, Measurement & Technology 4, no. 3 (May 1, 2010): 105–14. http://dx.doi.org/10.1049/iet-smt.2008.0138.

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Gabler, Lee F., Jeff R. Crandall, and Matthew B. Panzer. "Development of a Second-Order System for Rapid Estimation of Maximum Brain Strain." Annals of Biomedical Engineering 47, no. 9 (December 4, 2018): 1971–81. http://dx.doi.org/10.1007/s10439-018-02179-9.

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da Rosa Zanatta, Mateus, Fábio Lúcio Lópes de Mendonça, Felix Antreich, Daniel Valle de Lima, Ricardo Kehrle Miranda, Giovanni Del Galdo, and João Paulo C. L. da Costa. "Tensor-based time-delay estimation for second and third generation global positioning system." Digital Signal Processing 92 (September 2019): 1–19. http://dx.doi.org/10.1016/j.dsp.2019.04.003.

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Huang, Jingli, Guorong Zhao, and Xiangyu Zhang. "MEMS gyroscope/TAM-integrated attitude estimation based on moving horizon estimation." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 231, no. 8 (June 13, 2016): 1451–59. http://dx.doi.org/10.1177/0954410016652920.

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To improve the accuracy of the attitude sensor micro electro mechanical system gyroscope in low cost satellite, a nonlinear moving horizon estimation algorithm based on micro-electro mechanical system gyroscope/three-axis magnetometer is proposed in this paper. First, a quaternion micro-electro mechanical system gyroscope/three-axis magnetometer-integrated attitude estimation model is established so as to improve the accuracy of micro-electro mechanical system gyroscope. Thanks to the concealment and autonomy, these two low cost sensors have great potential in the military area. Second, taking advantage of optimal problem in coping with constraints, a real time moving horizon estimation algorithm with equality constraint is designed to deal with the disability of solving quaternion normalization analytically in the frame work of Kalman. In this algorithm, Gauss–Newton iterative method is used to obtain the optimal state estimation in the “window”. Meanwhile, strong tracking filter of arrival cost is designed outside of the “window” to enhance system robustness for that three-axis magnetometer is vulnerable to external interference. Third, the proposed MHE is applied in the micro-electro mechanical system gyroscope/three-axis magnetometer attitude estimation system. The simulation results show that the method has higher accuracy and robustness.

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Li, Yifei. "A Design Method of Virtual Folk Museum Roaming System Based on Visual Interaction Technology." Mathematical Problems in Engineering 2022 (May 14, 2022): 1–9. http://dx.doi.org/10.1155/2022/5059511.

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The effective display of museums can greatly improve the attention of museums. The traditional museum display methods are old and old-fashioned. Aiming at the lack of vivid and immersive display in folklore museums, based on augmented reality technology and artificial intelligence, a virtual folklore museum roaming system based on visual interaction technology is proposed for 3D visualization of cultural heritage. The method applies the 6D pose estimation algorithm of objects to the display of museum objects. 6D pose estimation of objects refers to detecting objects present in an image and estimating their 3D position and orientation relative to the observer. In the field of augmented reality, 6D pose estimation is used to measure the pose of objects in the real environment and add virtual objects to it with the correct pose, thereby realizing augmented reality applications on the mobile side. The experimental results show that the 6D pose estimation method proposed in this paper has an accuracy rate of 93.3% and a running speed of 30 frames per second, which meets the needs of augmented reality applications and can be used in augmented reality museum display systems to provide them with vivid interactive content. Breaking through the time and space limitations of cultural heritage objects, it brings an immersive visiting experience to the audience.

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BALAMETOV, Ashraf B., Elman D. KHALILOV, Afaq K. SALIMOVA, and Tarana M. ISAYEVA. "State Estimation of an AC Overhead Power Line Using the Relinearization Method." Elektrichestvo 4, no. 4 (2021): 17–24. http://dx.doi.org/10.24160/0013-5380-2021-4-17-24.

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As is well known, dispatch control centers receive information about the electric power system operation mode from a supervisory control and data acquisition system (SCADA) and phasor measurement units (PMU) in the form of remote measurements and remote signals. The remote measurements contain information on the power system operating parameters, and remote signals contain information on the positions of switching equipment. The controlled facility state estimation problem is conventionally solved using iteration methods because the system of state equations is nonlinear in nature. The application of the Kipnis-Shamir method makes it possible to transform the nonlinear system of algebraic equations into a linear system in a non-iterative manner by replacing quadratic state variables, after which the obtained linear system is solved parametrically. By applying a second transformation of variables, the system of algebraic equations is transformed into a second system of linear equations, after which the solution of this system and the quadratic system of linear equations, and, hence, also the initial system of nonlinear equations are found. The application of the non-iterative approach is considered on the example of estimating the state of a 500 kV overhead power line.

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Chen, Lijuan, Zihao Zhang, Yapeng Zhang, Xiaoshuang Xiong, Fei Fan, and Shuangbao Ma. "Research on Projection Filtering Method Based on Projection Symmetric Interval and Its Application in Underwater Navigation." Symmetry 13, no. 9 (September 16, 2021): 1715. http://dx.doi.org/10.3390/sym13091715.

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For non-linear systems (NLSs), the state estimation problem is an essential and important problem. This paper deals with the nonlinear state estimation problems in nonlinear and non-Gaussian systems. Recently, the Bayesian filter designer based on the Bayesian principle has been widely applied to the state estimation problem in NLSs. However, we assume that the state estimation models are nonlinear and non-Gaussian, applying traditional, typical nonlinear filtering methods, and there is no precise result for the system state estimation problem. Therefore, the larger the estimation error, the lower the estimation accuracy. To perfect the imperfections, a projection filtering method (PFM) based on the Bayesian estimation approach is applied to estimate the state. First, this paper constructs its projection symmetric interval to select the basis function. Second, the prior probability density of NLSs can be projected into the basis function space, and the prior probability density solution can be solved by using the Fokker–Planck Equation (FPE). According to the Bayes formula, the proposed estimator utilizes the basis function in projected space to iteratively calculate the posterior probability density; thus, it avoids calculating the partial differential equation. By taking two illustrative examples, it is also compared with the traditional UKF and PF algorithm, and the numerical experiment results show the feasibility and effectiveness of the novel nonlinear state estimation filter algorithm.

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Hernández-González, O., M. E. Guerrero-Sánchez, M. Farza, C. M. Astorga-Zaragoz, O. Barreto-Arenas, and F. Ramírez-Rasgado. "Observer-based supervision of the cardiovascular system with delayed measurements." Memorias del Congreso Nacional de Control Automático 5, no. 1 (October 17, 2022): 380–85. http://dx.doi.org/10.58571/cnca.amca.2022.064.

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This paper presents the design of a chain observer for monitoring the cardiovascular system. The system presents delays in the measured output. The chain observer proposed in this work is capable of estimating the free-delay state vector. The structure of the observer consists of two subsystems: the first subsystem at the base estimates the state vector with delay and by means of the second subsystem it is possible to estimate the delay-free state vector. {The proposed observer is applied for monitoring the dynamics of the cardiovascular system by obtaining the estimation of the state vector that is not available and reconstructing the output signal.

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Wang, Shuai, Fei Chen, Yongye Zhao, and Chuanbao Wang. "Estimation of decay rates to large-solutions of 3D compressible magnetohydrodynamic system." Journal of Mathematical Physics 63, no. 11 (November 1, 2022): 111507. http://dx.doi.org/10.1063/5.0096472.

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The aim of this paper is to get an estimation of decay rates to first-order and second-order derivatives of space for large-solutions to 3D compressible magnetohydrodynamic system. While the condition ( σ0 − 1, u0, Q0) ∈ L1 ∩ H2 is satisfied via a classical energy method and Fourier splitting method, first-order and second-order derivatives of space for large-solutions tending to 0 by L2-rate [Formula: see text] are shown. It is a necessary supplement to the result of Gao, Wei, and Yao [Appl. Math. Lett. 102, 106100 (2020)] in which they only obtained an estimation of decay rates to magnetic fields. Meanwhile, compared with the work of Gao, Wei, and Yao [Physica D 406, 132506 (2020)], we find that the appearance of magnetic fields does not have any bad effect on the estimation of decay rates to both the velocity field and density.

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Harakeh, Ali, Daniel Asmar, and Elie Shammas. "Self-supervised free space estimation in outdoor terrain." Robotica 36, no. 9 (June 1, 2018): 1278–300. http://dx.doi.org/10.1017/s0263574718000371.

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SUMMARYThe ability to reliably estimate free space is an essential requirement for efficient and safe robot navigation. This paper presents a novel system, built upon a stochastic framework, which estimates free space quickly from stereo data, using self-supervised learning. The system relies on geometric data in the close range of the robot to train a second-stage appearance-based classifier for long range areas in a scene. Experiments are conducted on board an unmanned ground vehicle, and the results demonstrate the advantages of the proposed technique over other self-supervised systems.

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Demetriou, Michael A., and Nikolaos Kazantzis. "Natural Observer Design for Singularly Perturbed Vector Second-Order Systems." Journal of Dynamic Systems, Measurement, and Control 127, no. 4 (December 13, 2004): 648–55. http://dx.doi.org/10.1115/1.2101847.

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Our aim in the present research study is to develop a systematic natural observer design framework for vector second-order systems in the presence of time-scale multiplicity. Specifically, vector second-order mechanical systems are considered along with fast sensor dynamics, and the primary objective is to obtain accurate estimates of the unmeasurable slow system state variables that are generated by an appropriately designed model-based observer. Within a singular perturbation framework, the proposed observer is designed on the basis of the system dynamics that evolves on the slow manifold, and the dynamic behavior of the estimation error that induces is analyzed and mathematically characterized in the presence of the unmodeled fast sensor dynamics. It is shown, that the observation error generated by neglecting the (unmodeled) fast sensor dynamics is of order O(ε), where ε is the singular perturbation parameter and a measure of the relative speed/time constant of the fast (sensor) and the slow component (vector second-order system) of the overall instrumented system dynamics. Finally, the performance of the proposed method and the convergence properties of the natural observer designed are evaluated in an illustrative example of a two-degree of freedom mechanical system.

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Cao, Ting, Huo-tao Gao, Chun-feng Sun, and Guo-bao Ru. "Differential Evolution Optimized a Second-Order Divided Difference Particle Filter." Journal of Electrical and Computer Engineering 2020 (February 24, 2020): 1–9. http://dx.doi.org/10.1155/2020/9541624.

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In order to improve the estimation accuracy of particle filter algorithm in a nonlinear system state estimation problem, a new algorithm based on the second-order divided difference filter to generate the proposed distribution and the differential evolution algorithm for resampling is proposed. The second-order divided difference based on Strling’s interpolation formula is used to generate approximations to nonlinear dynamics, which avoids the evaluation of the Jacobian derivative matrix and is easy to implement. Cholesky factorization is used to ensure the positive definiteness of the covariance matrix. The truncated errors of the local linearization are reduced to a certain extent, and the approximation degree of the proposed distribution to the posterior probability of the system state is improved. The differential evolution algorithm is used to replace the traditional resampling algorithm, which effectively mitigates the problem of particle degradation. Monte Carlo simulation experiments show the effectiveness of the new algorithm.

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Journal articles on the topic 'Second system of Estimation'

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