Готові списки джерел за темами / Plant-model mismatch compensation

Добірка наукової літератури з теми "Plant-model mismatch compensation"

Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Plant-model mismatch compensation"

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Koryakovskiy, Ivan, Manuel Kudruss, Heike Vallery, Robert Babuska, and Wouter Caarls. "Model-Plant Mismatch Compensation Using Reinforcement Learning." IEEE Robotics and Automation Letters 3, no. 3 (July 2018): 2471–77. http://dx.doi.org/10.1109/lra.2018.2800106.

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Li, Bingyun, Chunyue Song, Yannan Wu, and Jun Zhao. "A New Adaptive Factor-Based Output Compensation Strategy for Offset Free Control of MLD–MPC with Model–Plant Mismatch." Industrial & Engineering Chemistry Research 60, no. 4 (January 21, 2021): 1709–18. http://dx.doi.org/10.1021/acs.iecr.0c04473.

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3

Liu and Zhao. "Robust Perturbation Observer-based Finite Control Set Model Predictive Current Control for SPMSM Considering Parameter Mismatch." Energies 12, no. 19 (September 27, 2019): 3711. http://dx.doi.org/10.3390/en12193711.

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Анотація:
In order to improve the dynamics of the surface-mounted permanent magnet synchronous motors (SPMSM) used in servo systems, finite control set model predictive current control (FCS-MPCC) methods have been widely adopted. However, because the FCS-MPCC is a model-based strategy, its performance highly depends on the machine parameters, such as the winding resistance, inductance and flux linkage. Unfortunately, the parameter mismatch problem is common due to the measurement precision and environmental impacts (e.g., temperature). To enhance the robustness of the SPMSM FCS-MPCC systems, this paper proposes a Lundberg perturbation observer that is seldom used in the FCS model predictive control situations to remove the adverse effects caused by resistance and inductance mismatch. Firstly, the system model is established, and the FCS-MPCC mechanism is illustrated. Based on the machine model, the sensitivity of the control algorithm to the parameter mismatch is discussed. Then, the Luenberger perturbation observer that can estimate the general disturbance arising from the parameter uncertainties is developed, and the stability of the observer is analyzed by using the discrete pole assignment technique. Finally, the proposed disturbance observer is incorporated into the FCS-MPCC prediction plant model for real-time compensation. Both simulation and experiments are conducted on a three-phase SPMSM, verifying that the proposed strategy has marked control performance and strong robustness.
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4

Zanoli, Silvia Maria, Crescenzo Pepe, Giacomo Astolfi, and Francesco Luzi. "Reservoir Advanced Process Control for Hydroelectric Power Production." Processes 11, no. 2 (January 17, 2023): 300. http://dx.doi.org/10.3390/pr11020300.

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Анотація:
The present work is in the framework of water resource control and optimization. Specifically, an advanced process control system was designed and implemented in a hydroelectric power plant for water management. Two reservoirs (connected through a regulation gate) and a set of turbines for energy production constitute the main elements of the process. In-depth data analysis was carried out to determine the control variables and the major issues related to the previous operation conduction of the plant. A tailored modelization process was conducted, and satisfactory fitting performances were obtained with linear models. In particular, first-principles equations were combined with data-based techniques. The achievement of a reliable model of the plant and the availability of reliable forecasts of the measured disturbance variables—e.g., the hydroelectric power production plan—motivated the choice of a control approach based on model predictive control techniques. A tailored methodology was proposed to account for model uncertainties, and an ad hoc model mismatch compensation strategy was designed. Virtual environment simulations based on meaningful scenarios confirmed the validity of the proposed approach for reducing water waste while meeting the water demand for electric energy production. The control system was commissioned for the real plant, obtaining significant performance and a remarkable service factor.
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5

Li, Lin, Jiadong Xiao, Yanbiao Zou, and Tie Zhang. "Time-optimal path tracking for robots a numerical integration-like approach combined with an iterative learning algorithm." Industrial Robot: the international journal of robotics research and application 46, no. 6 (October 21, 2019): 763–78. http://dx.doi.org/10.1108/ir-03-2019-0063.

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Анотація:
Purpose The purpose of this paper is to propose a precise time-optimal path tracking approach for robots under kinematic and dynamic constraints to improve the work efficiency of robots and guarantee tracking accuracy. Design/methodology/approach In the proposed approach, the robot path is expressed by a scalar path coordinate and discretized into N points. The motion between two neighbouring points is assumed to be uniformly accelerated motion, so the time-optimal trajectory that satisfies constraints is obtained by using equations of uniformly accelerated motion instead of numerical integration. To improve dynamic model accuracy, the Coulomb and viscous friction are taken into account (while most publications neglect these effects). Furthermore, an iterative learning algorithm is designed to correct model-plant mismatch by adding an iterative compensation item into the dynamic model at each discrete point before trajectory planning. Findings An experiment shows that compared with the sequential convex log barrier method, the proposed numerical integration-like (NI-like) approach has less computation time and a smoother planning trajectory. Compared with the experimental results before iteration, the torque deviation, tracking error and trajectory execution time are reduced after 10 iterations. Originality/value As the proposed approach not only yields a time-optimal solution but also improves tracking performance, this approach can be used for any repetitive robot tasks that require more rapidity and less tracking error, such as assembly.
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Zhang, Fan, Yali Xue, Bin Wei, and Bing Zhang. "Model predictive control for gas turbine shaft speed based on model compensation using extended state observer." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, September 29, 2022, 095965182211275. http://dx.doi.org/10.1177/09596518221127511.

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Анотація:
Gas turbine engines have offered advanced power generation with relatively small size on marine vessels. The operational flexibility has high control requirements for shaft speed regulation. Model predictive control provides a methodology for safe and efficient operation of gas turbines. However, when working at partial load, the controller degrades due to the mismatch between predictive model in model predictive control and dynamics of gas turbine. To deal with the issue of model adaptability in model predictive control, model compensation–based model predictive control is proposed for the gas turbine operation. The dynamics of the plant is modified by the extended state observer to get close to the pure integrator. The model predictive control is devised based on the modified plant. The wide-range load regulation and disturbance rejection of gas turbine have been improved by leveraging the benefits of model compensation–based model predictive control.
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7

Yuan, Yuan, X. Chen, and J. Tang. "Disturbance Observer-Based Pitch Control of Wind Turbines for Enhanced Speed Regulation." Journal of Dynamic Systems, Measurement, and Control 139, no. 7 (May 9, 2017). http://dx.doi.org/10.1115/1.4035741.

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Анотація:
Time-varying unknown wind disturbances influence significantly the dynamics of wind turbines. In this research, we formulate a disturbance observer (DOB) structure that is added to a proportional-integral-derivative (PID) feedback controller, aiming at asymptotically rejecting disturbances to wind turbines at above-rated wind speeds. Specifically, our objective is to maintain a constant output power and achieve better generator speed regulation when a wind turbine is operated under time-varying and turbulent wind conditions. The fundamental idea of DOB control is to conduct internal model-based observation and cancelation of disturbances directly using an inner feedback control loop. While the outer-loop PID controller provides the basic capability of suppressing disturbance effects with guaranteed stability, the inner-loop disturbance observer is designed to yield further disturbance rejection in the low frequency region. The DOB controller can be built as an on–off loop, that is, independent of the original control loop, which makes it easy to be implemented and validated in existing wind turbines. The proposed algorithm is applied to both linearized and nonlinear National Renewable Energy Laboratory (NREL) offshore 5-MW baseline wind turbine models. In order to deal with the mismatch between the linearized model and the nonlinear turbine, an extra compensator is proposed to enhance the robustness of augmented controller. The application of the augmented DOB pitch controller demonstrates enhanced power and speed regulations in the above-rated region for both linearized and nonlinear plant models.
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Тези доповідей конференцій з теми "Plant-model mismatch compensation"

1

Noury, Keyvan, and Bingen Yang. "Analytical Statistical Study of Linear Parallel Feedforward Compensators for Nonminimum-Phase Systems." In ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9126.

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Анотація:
Abstract In this work, a new parallel feedforward compensator for the feedback loop of a linear nonminimum-phase system is introduced. Then, analytical statistical arguments between the existing developed methods and the innovated method are brought. The compelling arguments suggest the parallel feedforward compensation with derivative (PFCD) method is a strong method even though at its first survey it seems to be optimistic and not pragmatic. While most of the existing methods offer an optimal integral of squared errors (ISE) for the closed-loop response of the nominal plant, the PFCD offers a finite ISE; in reality, typically, the nominal plant is not of main concern in the controller design and the performance in the presence of mismatch model, noise, and disturbance has priority. In this work, there are several arguments brought to bold the importance of the innovated PFCD design. Also, there is a closed-loop design example to show the PFCD effectiveness in action.
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