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Journal articles on the topic 'Feedforward'

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Author: Grafiati

Published: 4 June 2021

Last updated: 11 March 2023

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1

Back, A. D., and A. C. Tsoi. "FIR and IIR Synapses, a New Neural Network Architecture for Time Series Modeling." Neural Computation 3, no. 3 (September 1991): 375–85. http://dx.doi.org/10.1162/neco.1991.3.3.375.

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A new neural network architecture involving either local feedforward global feedforward, and/or local recurrent global feedforward structure is proposed. A learning rule minimizing a mean square error criterion is derived. The performance of this algorithm (local recurrent global feedforward architecture) is compared with a local-feedforward global-feedforward architecture. It is shown that the local-recurrent global-feedforward model performs better than the local-feedforward global-feedforward model.

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2

Douglas, Michael R. "Holomorphic feedforward networks." Pure and Applied Mathematics Quarterly 18, no. 1 (2022): 251–68. http://dx.doi.org/10.4310/pamq.2022.v18.n1.a7.

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3

Hovd, Morten, and Robert R. Bitmead. "Feedforward for stabilization." IFAC Proceedings Volumes 42, no. 11 (2009): 602–6. http://dx.doi.org/10.3182/20090712-4-tr-2008.00097.

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4

Conaghan, P., and A. Lockey. "Feedback to feedforward." Notfall + Rettungsmedizin 12, S2 (September 2009): 45–48. http://dx.doi.org/10.1007/s10049-009-1222-1.

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5

Kluger, Avraham N., and Dina Nir. "The feedforward interview." Human Resource Management Review 20, no. 3 (September 2010): 235–46. http://dx.doi.org/10.1016/j.hrmr.2009.08.002.

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6

Hirose, Noriaki, and Ryosuke Tajima. "Deadbeat Feedforward Compensation with Frequency Shaping of Position Feedforward Controller." IEEJ Journal of Industry Applications 6, no. 2 (2017): 100–106. http://dx.doi.org/10.1541/ieejjia.6.100.

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7

Xia, Lian, Jing Qiu, and Jiang Han. "Linear Motor Control Algorithm and Experimental Research Based on Feedforward Fuzzy PID." Key Engineering Materials 620 (August 2014): 363–68. http://dx.doi.org/10.4028/www.scientific.net/kem.620.363.

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In this paper, theory analysis, the MATLAB research and experimental verification about feedforward fuzzy PID control have been performed by combining the characteristics of the PID, feedforward control and fuzzy control. Simulation results show that the feedforward fuzzy PID control could improve the response speed of the system and reduce the tracking error of the system which shows the obvious superiority compared with the PID, feedforward PID, and fuzzy PID. Load experiment for such four kinds of control modes is done on the linear motor platform, and the experimental results show that the accuracy of the feedforward fuzzy PID control is obviously higher than the other three kinds of control modes and the feedforward fuzzy PID control is easier to be implemented. The position error of feedforward fuzzy PID control is changeless during the load change, and the change of the speed tracking error is small, which proves that the feedforward fuzzy PID control is suitable for the condition of load change or the great disturbance.

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8

MANGAL, MANISH, and MANU PRATAP SINGH. "ANALYSIS OF MULTIDIMENSIONAL XOR CLASSIFICATION PROBLEM WITH EVOLUTIONARY FEEDFORWARD NEURAL NETWORKS." International Journal on Artificial Intelligence Tools 16, no. 01 (February 2007): 111–20. http://dx.doi.org/10.1142/s0218213007003229.

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This paper describes the application of two evolutionary algorithms to the feedforward neural networks used in classification problems. Besides of a simple backpropagation feedforward algorithm, the paper considers the genetic algorithm and random search algorithm. The objective is to analyze the performance of GAs over the simple backpropagation feedforward in terms of accuracy or speed in this problem. The experiments considered a feedforward neural network trained with genetic algorithm/random search algorithm and 39 types of network structures and artificial data sets. In most cases, the evolutionary feedforward neural networks seemed to have better of equal accuracy than the original backpropagation feedforward neural network. We found few differences in the accuracy of the networks solved by applying the EAs, but found ample differences in the execution time. The results suggest that the evolutionary feedforward neural network with random search algorithm might be the best algorithm on the data sets we tested.

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9

Alekseev, A. A., and V. V. Tyutikov. "Method for tuning feedforward in electric feed drive control systems." Vestnik IGEU, no. 6 (December 28, 2021): 45–53. http://dx.doi.org/10.17588/2072-2672.2021.6.045-053.

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The electric feed drive used in metal-cutting machines like any high-precision electric drive requires high accuracy of reference processing and robustness against perturbations. For this purpose, feedforwards are added to the position controller to improve set point processing time and to compensate for disturbances. Feedforwards are usually tuned manually when the machine is setup, either by applying a series of tests on the motor or by calculation. The calculation requires some information about the magnitudes of disturbances that can be compensated by appropriate feedforwards, but this information is not always available a priori. In this paper, we propose tuning the feedforward coefficients based on the results of the parametric identification of the values of the torques acting on the electric drive, as well as the apparent moment of inertia. For parametric identification the methods of electric drive theory, method of least squares, and digital signal processing method are used; mathematical modeling method is applied to assess the compensation quality. The authors propose the method of tuning the parameters of the control system of electric feed drive based on parametric identification of the values of torques acting on the motor and/or the operating device. The results of control system simulation show both high identification accuracy and significant reduction of dynamic control error when feedforwards are activated. The considered structure of the control system and the proposed algorithm of identification and adjustment of its parameters can be used in electric drives of metal-cutting machine tools. The simulation results have shown that the use of feedforwards, tuned in accordance with the algorithm, enable to reduce the dynamic position tracking error by more than 50 times, which can be critical in contour machining.

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10

Jensen, Konrad Johan, Morten Kjeld Ebbesen, and Michael Rygaard Hansen. "Adaptive Feedforward Control of a Pressure Compensated Differential Cylinder." Applied Sciences 10, no. 21 (November 5, 2020): 7847. http://dx.doi.org/10.3390/app10217847.

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This paper presents the design, simulation and experimental verification of adaptive feedforward motion control for a hydraulic differential cylinder. The proposed solution is implemented on a hydraulic loader crane. Based on common adaptation methods, a typical electro-hydraulic motion control system has been extended with a novel adaptive feedforward controller that has two separate feedforward states, i.e, one for each direction of motion. Simulations show convergence of the feedforward states, as well as 23% reduction in root mean square (RMS) cylinder position error compared to a fixed gain feedforward controller. The experiments show an even more pronounced advantage of the proposed controller, with an 80% reduction in RMS cylinder position error, and that the separate feedforward states are able to adapt to model uncertainties in both directions of motion.

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11

Huang, Peichen, Zhigang Zhang, and Xiwen Luo. "Feedforward-plus-proportional–integral–derivative controller for agricultural robot turning in headland." International Journal of Advanced Robotic Systems 17, no. 1 (January 1, 2020): 172988141989767. http://dx.doi.org/10.1177/1729881419897678.

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Traveling along straight lines and headland turning are two common motions during the automatic guidance of agricultural machines. However, most studies focus on accurately following parallel tracks in the field and seldom consider the maneuvers at the end of each row. Moreover, numerous studies have mainly focused on planning the global trajectories in the entire field to increase field efficiency, and very few works are related to maneuver generation and vehicle control in headlands. In this study, a feedforward-plus-proportional–integral–derivative controller for a differential drive robot in headland turning was developed. The feedforward-plus-proportional–integral–derivative controller consisted of a feedforward and a feedback loop. The feedforward loop was designed based on the heading errors of a lookahead point on the planning path. The feedback loop was designed based on radial errors to improve the tracking accuracy. Field comparison tests of feedforward, feedback, and feedforward-plus-proportional–integral–derivative controllers were conducted. Experimental results showed that the feedforward-plus-proportional–integral–derivative had better tracking results and took less turning time.

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12

Dulfer, Nicky, and Firoozeh Akhlaghi Koopaei. "Moving from Feedback to Feedforward in IBDP classrooms." Journal of Research in International Education 20, no. 2 (July 27, 2021): 101–13. http://dx.doi.org/10.1177/14752409211032528.

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There is widespread acceptance of the positive impact of constructive feedback on students’ learning progress. However, few studies investigate the role of feedforward in high-stakes learning environments. This research explores feedback and feedforward practices in International Baccalaureate Diploma Programme classrooms in Hong Kong and Australia. The article analyses 18 teachers’ practices and perceptions about feedback and feedforward. The teachers’ perceptions on feedforward were analysed using a survey and semi-structured interviews, while their teaching practices were evaluated using a lesson observation instrument. Results indicated that participants were aware of the importance of providing feedforward techniques and tools in the classroom to support students in closing the gaps between their current performance and desired performance. Not all teachers, however, incorporated feedforward in all their lessons as a learning tool or differentiation strategy to enhance students’ learning experience and assessment outcomes.

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13

Songyuan, Deng, and Zhao Xia. "An improving control strategy for grid -connected current in weak grid." E3S Web of Conferences 252 (2021): 01010. http://dx.doi.org/10.1051/e3sconf/202125201010.

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The traditional proportional feedforward control strategy can suppress the low order harmonics in the strong power grid, but in the weak power grid environment, the grid impedance will have an adverse impact on the stability of the system, resulting in the proportional feedforward control can not suppress the low order harmonics well. In order to solve this problem, a control strategy combining resonant feedforward and new repetitive proportional controller is proposed. Firstly, the stability of traditional proportional feedforward and resonant feedforward systems is analyzed and compared by impedance analysis method. Then, a new repetitive controller is added to suppress low order harmonics based on resonant feedforward control, and the stability of single-phase LCL grid connected inverter system is analyzed Matlab / Simulink is used to simulate and verify the system. The results show that the system stability and the ability to suppress low order harmonics are significantly improved.

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14

Navarre, David, Philippe Palanque, Sven Coppers, Kris Luyten, and Davy Vanacken. "Model-based Engineering of Feedforward Usability Function for GUI Widgets." Interacting with Computers 33, no. 1 (January 2021): 73–91. http://dx.doi.org/10.1093/iwcomp/iwab014.

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Abstract Feedback and feedforward are two fundamental mechanisms that support users’ activities while interacting with computing devices. While feedback can be easily solved by providing information to the users following the triggering of an action, feedforward is much more complex as it must provide information before an action is performed. For interactive applications where making a mistake has more impact than just reduced user comfort, correct feedforward is an essential step toward correctly informed, and thus safe, usage. Our approach, Fortunettes, is a generic mechanism providing a systematic way of designing feedforward addressing both action and presentation problems. Including a feedforward mechanism significantly increases the complexity of the interactive application hardening developers’ tasks to detect and correct defects. We build upon an existing formal notation based on Petri Nets for describing the behavior of interactive applications and present an approach that allows for adding correct and consistent feedforward.

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15

Johnson, Kristin A., Shojiro Nozu, and Richard K. Shields. "Trunk Angle Modulates Feedforward and Feedback Control during Single-Limb Squatting." Journal of Functional Morphology and Kinesiology 6, no. 4 (October 7, 2021): 82. http://dx.doi.org/10.3390/jfmk6040082.

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Trunk positioning and unexpected perturbations are high-risk conditions at the time of anterior cruciate ligament injury. The influence of trunk positioning on motor control responses to perturbation during dynamic performance is not known. We tested the influence of trunk position on feedforward and feedback control during unexpected perturbations while performing a novel single-limb squatting task. We also assessed the degree that feedforward control was predictive of feedback responses. In the flexed trunk condition, there were increased quadriceps (p < 0.026) and gluteus medius long-latency reflexes (p < 0.001) and greater quadriceps-to-hamstrings co-contraction during feedforward (p = 0.017) and feedback (p = 0.007) time bins. Soleus long-latency reflexes increased more than 100% from feedforward muscle activity regardless of trunk condition. Feedforward muscle activity differentially predicted long-latency reflex responses depending on the muscle (R2: 0.47–0.97). These findings support the concept that trunk positioning influences motor control responses to perturbation and that feedback responses may be invariant to the feedforward control strategy.

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16

von der Gracht, Sören, Eddie Nijholt, and Bob Rink. "Amplified steady state bifurcations in feedforward networks." Nonlinearity 35, no. 4 (March 7, 2022): 2073–120. http://dx.doi.org/10.1088/1361-6544/ac5463.

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Abstract We investigate bifurcations in feedforward coupled cell networks. Feedforward structure (the absence of feedback) can be defined by a partial order on the cells. We use this property to study generic one-parameter steady state bifurcations for such networks. Branching solutions and their asymptotics are described in terms of Taylor coefficients of the internal dynamics. They can be determined via an algorithm that only exploits the network structure. Similar to previous results on feedforward chains, we observe amplifications of the growth rates of steady state branches induced by the feedforward structure. However, contrary to these earlier results, as the interaction scenarios can be more complicated in general feedforward networks, different branching patterns and different amplifications can occur for different regions in the space of Taylor coefficients.

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17

Rudenko, Oleg G., and Alexander A. Bezsonov. "Coevolving Feedforward Neural Networks." Journal of Automation and Information Sciences 48, no. 9 (2016): 36–48. http://dx.doi.org/10.1615/jautomatinfscien.v48.i9.30.

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18

Chen, K., V. Kvasnicka, P. C. Kanen, and S. Haykin. "Feedforward Neural Network Methodology." IEEE Transactions on Neural Networks 12, no. 3 (May 2001): 647–48. http://dx.doi.org/10.1109/tnn.2001.925573.

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19

Dowrick, Peter W., Weol Soon Kim-Rupnow, and Thomas J. Power. "Video Feedforward for Reading." Journal of Special Education 39, no. 4 (February 2006): 194–207. http://dx.doi.org/10.1177/00224669060390040101.

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20

Candes, Emmanuel J., and Terrence L. Fine. "Feedforward Neural Network Methodology." Journal of the American Statistical Association 95, no. 450 (June 2000): 682. http://dx.doi.org/10.2307/2669423.

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21

Oberst, M., and R. Weigel. "Delta–Sigma feedforward topology." Electronics Letters 44, no. 8 (2008): 514. http://dx.doi.org/10.1049/el:20080640.

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22

Lynch, Michael. "Feedforward loop for diversity." Nature 523, no. 7561 (July 2015): 414–16. http://dx.doi.org/10.1038/nature14634.

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23

Levin, Asriel U., and Kumpati S. Narendra. "Identification Using Feedforward Networks." Neural Computation 7, no. 2 (March 1995): 349–69. http://dx.doi.org/10.1162/neco.1995.7.2.349.

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This paper is concerned with the identification of an unknown nonlinear dynamic system when only the inputs and outputs are accessible for measurement. Specifically we investigate the use of feedforward neural networks as models for the input-output behavior of such systems. Relying on the approximation capabilities of feedforward neural networks and under mild assumptions regarding the properties of the underlying nonlinear system, it is shown that there exists a feedforward network that for almost all inputs (an open and dense set) will display the input-output behavior of the system.

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24

Rao, M. B. "Feedforward Neural Network Methodology." Technometrics 42, no. 4 (November 2000): 432–33. http://dx.doi.org/10.1080/00401706.2000.10485725.

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25

Sternad, Mikael, and Torsten Söderström. "LQG-optimal feedforward regulators." Automatica 24, no. 4 (July 1988): 557–61. http://dx.doi.org/10.1016/0005-1098(88)90100-8.

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26

Chyung, D. H. "Feedforward digital tracking controller." IEEE Transactions on Automatic Control 36, no. 10 (1991): 1199–20. http://dx.doi.org/10.1109/9.90236.

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27

Kenington, P. B. "Efficiency of feedforward amplifiers." IEE Proceedings G Circuits, Devices and Systems 139, no. 5 (1992): 591. http://dx.doi.org/10.1049/ip-g-2.1992.0091.

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28

Carrasco, Diego S., and Graham C. Goodwin. "Feedforward model predictive control." Annual Reviews in Control 35, no. 2 (December 2011): 199–206. http://dx.doi.org/10.1016/j.arcontrol.2011.10.007.

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29

Sun, Yixiu, Xiaoqing Li, Ying Luo, Xuedong Chen, and Lizhan Zeng. "Iterative Tuning of Feedforward Controller with Precise Time-Delay Compensation for Precision Motion System." Mathematical Problems in Engineering 2020 (October 28, 2020): 1–23. http://dx.doi.org/10.1155/2020/9391526.

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The accuracy of feedforward control model including system time-delay significantly affects the position tracking performance in a precision motion system. In this paper, an iterative tuning method for feedforward control with precise time-delay compensation is proposed. First, considering system time-delay from actuator, sensor, calculation, and communication in real platform, a feedforward control model with time-delay compensation is established, and a nonlinear objective function with time-delay is designed based on the measured data of a finite time task, to minimize the position tracking error. Second, in order to deal with both the nonlinear objective function and also unknown disturbances and noise in the real system, an optimization strategy combining the Gauss–Newton iterative (GNI) scheme and instrumental variable (IV) is proposed to realize the unbiased estimation of the feedforward parameters and precise delay time. Finally, with the identified feedforward control parameters, the precise system time-delay which is a nonintegral multiple of the sampling period is compensated accurately for the feedforward control with accurate path planning time-shift in the implementation. The effectiveness of the proposed feedforward parameter tuning and precise time-delay compensation scheme is verified by the simulation and also experimental result on a precision motion platform with obvious position tracking performance improvement.

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30

Koo, Min-Sung, Ho-Lim Choi, and Jong-Tae Lim. "Adaptive Control of a Class of Feedforward and Non-feedforward Nonlinear Systems." Journal of Institute of Control, Robotics and Systems 17, no. 6 (June 1, 2011): 573–78. http://dx.doi.org/10.5302/j.icros.2011.17.6.573.

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31

Koo, Min-Sung, and Ho-Lim Choi. "Measurement Feedback Control of Nonlinear Systems with Non-Feedforward and Feedforward Nonlinearities." Journal of Institute of Control, Robotics and Systems 24, no. 6 (June 30, 2018): 496–500. http://dx.doi.org/10.5302/j.icros.2018.0028.

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32

Koo, Min-Sung, and Ho-Lim Choi. "Measurement Feedback Control of Nonlinear Systems with Non-Feedforward and Feedforward Nonlinearities." Journal of Institute of Control, Robotics and Systems 24, no. 6 (June 30, 2018): 496–500. http://dx.doi.org/10.5302/j.icros.2018.18.0028.

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33

Zhang, Jin Guang, Nan Xiang, Zuo Chao Xiao, and Guo Ping Ding. "Research on Adaptive Feedforward Control Algorithm of Electromagnetic Active Vibration Isolation System." Applied Mechanics and Materials 150 (January 2012): 80–84. http://dx.doi.org/10.4028/www.scientific.net/amm.150.80.

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Feedforward control method to control vibration in the active vibration isolation system was discussed. By introducing the FIR filter as the feedforward link, using the mean-square deviation of system error as the performance index and utilizing the LMS algorithm to obtain the optimal parameters of controller, the design of adaptive feedforward controller was fulfilled. The simulation results showed that: for the active vibration isolation system with regularly vibration source, adopting adaptive filter method of feedforward control has notable effect. The contrast experiment with using the PID controller further verified the simulation results.

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34

Berg, Matias, and Tomi Roinila. "Dynamic Effect of Input-Voltage Feedforward in Three-Phase Grid-Forming Inverters." Energies 13, no. 11 (June 7, 2020): 2923. http://dx.doi.org/10.3390/en13112923.

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Grid-connected and grid-forming inverters play essential roles in the utilization of renewable energy. One problem of such a converter system is the voltage deviations in the DC-link between the source and the inverter that can disrupt the inverter output voltage. A common method to prevent these voltage deviations is to apply an input-voltage feedforward control. However, the feedforward control has detrimental effects on the inverter dynamics. It is shown that the effect of the feedforward in the input-to-output dynamics is not ideal due to the delay in the digital control system. The delay affects the input-to-output dynamics at high frequencies, and only a minor improvement can be achieved by low-pass filtering the feedforward control signal. Furthermore, the feedforward control can remarkably affect the inverter input admittance, and therefore, impedance-based stability problems may arise at the DC interface. This paper proposes a method based on linearization and extra element theorem to model the effect of the feedforward control in the inverter dynamics. Experimental measurements are shown to demonstrate the effectiveness of the proposed model.

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35

Miyashiro, J. K., and E. O. Feigl. "A model of combined feedforward and feedback control of coronary blood flow." American Journal of Physiology-Heart and Circulatory Physiology 268, no. 2 (February 1, 1995): H895—H908. http://dx.doi.org/10.1152/ajpheart.1995.268.2.h895.

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Recent evidence shows that norepinephrine affects coronary blood flow not only by alpha-receptor-mediated vasoconstriction and by feedback metabolic vasodilation that occurs as a result of myocardial beta-receptor activation, but also by the direct activation of coronary vascular beta-receptors that increase flow in a feedforward manner. The implications of combined feedforward and feedback control in maintaining the balance between metabolism and flow were investigated in the present mass balance model. Feedback was represented by a closed loop and was based on the hypothesis that the regulated variables are myocardial PO2 and PCO2 and that divergence of these variables from their operating point values functions as the metabolic error signals that manipulate coronary vascular smooth muscle and flow to match metabolism. alpha-Receptor-mediated vasoconstriction and beta-receptor-mediated vasodilation are represented by feedforward open loops that are activated simultaneously with increases in metabolism. The postulated control schemes of 1) metabolic feedback control alone, 2) feedback plus alpha- and beta-adrenergic feedforward control, and 3) feedback plus beta-adrenergic feedforward control were able to simulate the steady-state increase in coronary flow and the decrease in coronary venous PO2 that occurs during comparable experimental conditions. The simulations demonstrate that 1) the speed and accuracy of the flow response improve as beta-adrenergic feedforward control is added and alpha-adrenergic feedforward control is removed from the control scheme, 2) high feedback gain also improves the accuracy of the flow response, but the penalty is instability, and 3) a lag in alpha-adrenergic feedforward control improves the stability of the coronary response.

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36

Vrečko, D., N. Hvala, and B. Carlsson. "Feedforward-feedback control of an activated sludge process: a simulation study." Water Science and Technology 47, no. 12 (June 1, 2003): 19–26. http://dx.doi.org/10.2166/wst.2003.0623.

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In this paper a simulated plant based on a wastewater treatment benchmark is used to evaluate a number of controllers. Feedforward-feedback controllers for dissolved oxygen set-point and external carbon flow, and feedforward controller for internal recycle flow are evaluated separately and altogether. In the feedforward parts of the controllers, static physical models are incorporated in the control laws. The feedback parts of the controllers are used to compensate for model approximations. A simulation study shows that feedforward-feedback control of the activated sludge plant is more successful than standard PI control in meeting the effluent standards and reducing operational costs.

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37

Tomizuka, Masayoshi. "Zero Phase Error Tracking Algorithm for Digital Control." Journal of Dynamic Systems, Measurement, and Control 109, no. 1 (March 1, 1987): 65–68. http://dx.doi.org/10.1115/1.3143822.

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A digital feedforward control algorithm for tracking desired time varying signals is presented. The feedforward controller cancels all the closed-loop poles and cancellable closed-loop zeros. For uncancellable zeros, which include zeros outside the unit circle, the feedforward controller cancels the phase shift induced by them. The phase cancellation assures that the frequency response between the desired output and actual output exhibits zero phase shift for all the frequencies. The algorithm is particularly suited to the general motion control problems including robotic arms and positioning tables. A typical motion control problem is used to show the effectiveness of the proposed feedforward controller.

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38

Choura, S. "On the Design of Finite Time Settling Control for Linear Systems." Journal of Dynamic Systems, Measurement, and Control 114, no. 3 (September 1, 1992): 359–68. http://dx.doi.org/10.1115/1.2897356.

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The design of controllers combining feedback and feedforward for the finite time settling control of linear systems, including linear time-varying systems, is considered. The feedforward part transfers the initial state of a linear system to a desired final state in finite time, and the feedback part reduces the effects of uncertainties and disturbances on the system performance. Two methods for determining the feedforward part, without requiring the knowledge of the explicit state solutions, are proposed. In the first method, a numerical procedure for approximating combined controls that drive linear time-varying systems to their final state in finite time is given. The feedforward part is a variable function of time and is selected based on a set of necessary conditions, such as magnitude constraints. In the second method, an analytical procedure for constructing combined controls for linear time-invariant systems is presented, where the feedforward part is accurately determined and it is of the minimum energy control type. It is shown that both methods facilitate the design of the feedforward part of combined controllers for the finite time settling of linear systems. The robustness of driving a linear system to its desired state in finite time is analyzed for three types of uncertainties. The robustness analysis suggests a modification of the feedforward control law to assure the robustness of the control strategy to parameter uncertainties for arbitrary final times.

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39

Cai, Xiao, Yulong Yin, and Qingfang Zhang. "A cross-language study on feedforward and feedback control of voice intensity in Chinese–English bilinguals." Applied Psycholinguistics 41, no. 4 (July 2020): 771–95. http://dx.doi.org/10.1017/s0142716420000223.

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AbstractSpeech production requires the combined efforts of feedforward and feedback control, but it remains unclear whether the relative weighting of feedforward and feedback control is organized differently between the first language (L1) and the second language (L2). In the present study, a group of Chinese–English bilinguals named pictures in their L1 and L2, while being exposed to multitalker noise. Experiment 1 compared feedforward control between L1 and L2 speech production by examining intensity increases in response to a masking noise (90 dB SPL). Experiment 2 compared feedback control between L1 and L2 speech production by examining intensity increases in response to a weak (30 dB SPL) or strong noise (60 dB SPL). We also examined a potential relationship between L2 fluency and the relative weighting of feedforward and feedback systems. The results indicated that L2 speech production relies less on feedforward control relative to L1, exhibiting attenuated Lombard effects to the masking noise. In contrast, L2 speech production relies more on feedback control than L1, producing larger Lombard effects to the weak and strong noise. The relative weighting of feedforward and feedback control is dynamically changed as second language learning progresses.

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40

Kim, Young-Choon, Ho-Bin Song, and Moon-Taek Cho. "Comparative Analysis of PI Controller and Disturbance Cancellation Observer of a Feedforward." Journal of the Korea Academia-Industrial cooperation Society 10, no. 12 (December 31, 2009): 3581–86. http://dx.doi.org/10.5762/kais.2009.10.12.3581.

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41

Clark, Robert L. "A Hybrid Autonomous Control Approach." Journal of Dynamic Systems, Measurement, and Control 117, no. 2 (June 1, 1995): 232–40. http://dx.doi.org/10.1115/1.2835184.

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A hybrid autonomous control approach for active damping and control of a persistent disturbance is presented. Direct velocity feedback control is coupled with an adaptive feedforward controller to minimize the transient response and that due to a persistent disturbance, respectively. A time-averaged gradient descent algorithm was selected to adapt the feedforward filter, rendering the controller model-insensitive and thus autonomous for the chosen application. The feedback control loop serves to increase the damping of the controlled structure, decreasing the convergence time associated with the adaptive feedforward filter. Thus the integration of the two control approaches affords increases in performance previously not possible with the adaptive feedforward controller alone.

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NUGROHO, MOCHAMAD ARI BAGUS, NOVIE AYUB WINDARKO, and BAMBANG SUMANTRI. "Perancangan Kendali Multilevel Inverter Satu Fasa Tiga Tingkat dengan PI+feedforward pada Beban Nonlinier." ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika 7, no. 3 (September 30, 2019): 493. http://dx.doi.org/10.26760/elkomika.v7i3.493.

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ABSTRAKSebuah konverter daya multilevel inverter diharapkan mampu untuk menyuplai tegangan AC ideal pada kondisi beban linier maupun nonlinier. Diharapkan metode kendali mampu cepat tanggap dan mampu mempertahankan bentuk tegangan AC keluaran inverter. Pengendali PI+feedforward diajukan dalam makalah ini. Pengendali ini akan diuji dengan beban linier maupun nonlinier. Beban nonlinier berupa rangkaian penyearah dengan filter kapasitor. Berdasarkan pengujian simulasi didapatkan bahwa pengendali PI+feedforward lebih cepat tanggap terhadap gangguan yang dibuktikan dengan nilai kesalahan rata-rata absolut sekitar 73% lebih kecil dari pengendali PI. Hasil Simulasi menunjukkan bahwa multilevel inverter dengan kendali PI menghasilkan THDv sebesar 0,669% pada beban linier dan sebesar 1,263% pada kondisi beban nonlinier. Sedangkan dengan kendali PI+feedforward menghasilkan THDv sebesar 0,292% pada beban linier dan sebesar 1,044% pada kondisi beban nonlinier.Kata kunci: mutilevel inverter, pengendali PI, feedforward, beban non-linier ABSTRACTA multilevel inverter power converter is expected to be able to supply ideal AC voltage in linear and nonlinear load conditions. It is expected that the control method is be able to respond quickly and be able to maintain the waveform of the inverter output AC voltage. PI + feedforward controller is proposed in this paper. This controller will be tested with linear and nonlinear loads. Nonlinear load is a rectifier circuit with a filter capacitor. Based on simulation it was found that PI + feedforward controllers were more responsive to interference as evidenced by the mean absolute error (MAE) value of about 73% less than the PI controller. Simulation results show that multilevel inverter with PI control produces THDv of 0.669% in linear load and 1.263% in nonlinear load conditions. Whereas with PI + feedforward control produces THDv of 0.292% in linear loads and of 1.044% in nonlinear load conditions.Keywords: multilevel inverter, PI controller, feedforward, non-linear load

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Wei, Zhouxiang, Zhiwen Huang, and Jianmin Zhu. "Position Control of Magnetic Levitation Ball Based on an Improved Adagrad Algorithm and Deep Neural Network Feedforward Compensation Control." Mathematical Problems in Engineering 2020 (December 21, 2020): 1–13. http://dx.doi.org/10.1155/2020/8935423.

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To control the position of the magnetic levitation ball more accurately, this paper proposes a deep neural network feedforward compensation controller based on an improved Adagrad optimization algorithm. The control structure of the controller consists of a deep neural network identifier, a deep neural network feedforward compensator, and a PID controller. First, the dynamic inverse model of the magnetic levitation ball is established by the deep neural network identifier which is trained online based on the improved Adagrad algorithm, and the trained network parameters are dynamically copied to the deep neural network feedforward compensator. Then, the position control of the magnetic levitation ball system is realized by the output of the feedforward compensator and the PID controller. Simulations and experiments illustrate that the accuracy of the deep network feedforward compensation control based on an improved Adagrad algorithm is higher, and its control system shows good dynamic and static performance and robustness to some extent.

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Li, Ke, Yeming Zhang, Shaoliang Wei, and Hongwei Yue. "Evolutionary Algorithm-Based Friction Feedforward Compensation for a Pneumatic Rotary Actuator Servo System." Applied Sciences 8, no. 9 (September 12, 2018): 1623. http://dx.doi.org/10.3390/app8091623.

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The friction interference in the pneumatic rotary actuator is the primary factor affecting the position accuracy of a pneumatic rotary actuator servo system. The paper proposes an evolutionary algorithm-based friction-forward compensation control architecture for improving position accuracy. Firstly, the basic equations of the valve-controlled actuator are derived and linearized in the middle position, and the transfer function of the system is further obtained. Then, the evolutionary algorithm-based friction feedforward compensation control architecture is structured, including that the evolutionary algorithm is used to optimize the controller coefficients and identify the friction parameters. Finally, the contrast experiments of four control strategies (the traditional PD control, the PD control with friction feedforward compensation without evolutionary algorithm tuning, the PD control with friction feedforward compensation based on the differential evolution algorithm, and the PD control with friction feedforward compensation based on the genetic algorithm) are carried out on the experimental platform. The experimental results reveal that the evolutionary algorithm-based friction feedforward compensation greatly improves the position tracking accuracy and positioning accuracy, and that the differential evolution-based case achieves better accuracy. Also, the system with the friction feedforward compensation still maintains high accuracy and strong stability in the case of load.

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Gelder, Edgar de, Marc van de Wal, Carsten Scherer, Camile Hol, and Okko Bosgra. "Nominal and Robust Feedforward Design With Time Domain Constraints Applied to a Wafer Stage." Journal of Dynamic Systems, Measurement, and Control 128, no. 2 (April 4, 2005): 204–15. http://dx.doi.org/10.1115/1.2192821.

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A new method is proposed to design a feedforward controller for electromechanical servo systems. The settling time is minimized by iteratively solving a linear programming problem. A bound on the amplitude of the feedforward control signal can be imposed and the McMillan degree of the controller can be fixed a priori. We choose Laguerre basis functions for the feedforward filter. Since finding the optimal pole location is very difficult, we present a computationally cheap method to determine the pole location that works well in practice. Furthermore, we show how the method can account for plant and/or reference signal uncertainty. Uncertainty in servo systems can usually be modeled by additive norm-bounded dynamic uncertainty. We will show that, because the feedforward controller is designed for a finite-time interval, we can replace the dynamic uncertainty set by a parametric one. This allows us to design a robust feedforward controller by solving an LMI problem, under the assumption that the transfer functions of the plant, sensitivity, and process sensitivity depend affinely on the uncertainty. If the uncertainty set is a finite set, which is usually the case for uncertainty in the reference profiles, the feedforward design problem reduces to a linear program. These classes of uncertainty sets are well suited to describe variations in the plant and in the reference profile of a wafer stage, which is important for the practical application of the filter. Experimental results for a wafer stage demonstrate the performance improvement compared to a standard inertia feedforward filter.

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Yin, Fang Chen, Geng Sheng Ma, Jia Xue Yu, Ya Feng Ji, Bo Wang, and Dian Hua Zhang. "The Optimization Plastic Coefficient in AWC Research and Application." Advanced Materials Research 941-944 (June 2014): 1221–24. http://dx.doi.org/10.4028/www.scientific.net/amr.941-944.1221.

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Aimed at the main factors of hot rolled strip steel product width fluctuation, rolled piece is put forward to plasticity coefficient and entrance width as the input variables of feedforward AWC control algorithm.Expounds a kind of optimization of plasticity coefficient Q feedforward AWC control system principle and plasticity coefficient Q of linear prediction algorithm.Field application shows that the Q prediction feedforward AWC has significant effect on inhibition of hot rolled strip width deviation.

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Zhao, Yongdong, and Suhada Jayasuriya. "Feedforward Controllers and Tracking Accuracy in the Presence of Plant Uncertainties." Journal of Dynamic Systems, Measurement, and Control 117, no. 4 (December 1, 1995): 490–95. http://dx.doi.org/10.1115/1.2801105.

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In the absence of plant parameter uncertainty feedforward controllers can be synthesized to achieve perfect continuous tracking. When plant has uncertainties it is, in general, impossible to achieve such perfect tracking. Investigated in this paper is the role played by feedforward controllers in the presence of plant uncertainties. We show that the use of feedforward controllers cannot improve the tracking error beyond what is achievable with a properly designed feedback loop, over all plant uncertainties. Including preview in the feedforward will not alter the situation either. We present two methods of designing robust compensators so that the tracking error due to uncertainties will be made small in some sense in the frequency domain and will have zero error in the steady state.

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Cardell, N. Scott, Wayne Joerding, and Ying Li. "Why Some Feedforward Networks Cannot Learn Some Polynomials." Neural Computation 6, no. 4 (July 1994): 761–66. http://dx.doi.org/10.1162/neco.1994.6.4.761.

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It seems natural to test feedforward networks on deterministic functions. Yet, some simple functions, notably polynomials, present some difficult problems for approximation by feedforward networks. The estimated parameters become unbounded and fail to follow any unique pattern. Furthermore, as the fit to the specified functions becomes closer, numerical problems may develop in the algorithm. This paper explains why these problems occur for polynomials of order less than or equal to the number of hidden units of a feedforward network. We show that other examples occur for functions mathematically related to the network's squashing function. These difficulties do not indicate problems with the training algorithm, but occur as an inherent consequence of the role of the connection weights in feedforward networks.

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Wang, Der-An, and Yii-Mai Huang. "Vibration Control of a Beam Using the Nearly Optimal Control Algorithm with a Disturbance Force Observer." Journal of Mechanics 17, no. 4 (December 2001): 173–77. http://dx.doi.org/10.1017/s1727719100001908.

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ABSTRACTActive vibration control of a flexible beam subjected to arbitrary, unmeasurable disturbance forces is investigated in this paper. The concept of independent modal space control is adopted. Both the feedforward and feedback control is implemented here to reduce the beam vibration. Because of the existence of the disturbance forces, the feedforward control is applied by employing the idea of force cancellation. A modal space disturbance force observer is then established in this paper to observe the disturbance modal forces for the feedforward control. For obtaining the feedforward and feedback control gains with the optimal sense, the nearly optimal control law is derived, where the modal disturbance forces are regarded as additional states. The vibration control performances and the asymptotic properties of the control law are discussed.

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Zhao, Kaijie, Sheng Zeng, and Liangliang Zhao. "Research on Tension Control System of Reciprocating Winding." Journal of Physics: Conference Series 2160, no. 1 (January 1, 2022): 012080. http://dx.doi.org/10.1088/1742-6596/2160/1/012080.

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Abstract When the enameled wire is winded onto the poles of the motor stator or rotor, the winding quality hugely relies on the control precision of the tension. Therefore, it is necessary to control the tension of the enameled wire in winding process. A tension control system is built with single chip microcomputer, the encoder and the servo motor. The PID feedback controller and feedforward controller are combined to form feedforward feedback controller, which using feedback information of swing angle deviation and feedforward information of wire frame position to adjust the pay off speed dynamically and control tension of enameled wire further. A procedural experimental modelling method is discussed in order to identify the feedforward model. The experiment is performed, it is found that in the typical situation of setting tension 1500 g, the tension fluctuation rate of the PID controller with feedforward model is only 2%, which is far better than that of pure PID controller with a fluctuation rate of 14%. The result shows that the proposed experimental modelling method hosts the characteristics of good accuracy, universality and applicability.

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