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Статті в журналах з теми "Input-output feedback linearization"

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Автор: Grafiati

Опубліковано: 8 червня 2024

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1

SLOTINE, JEAN-JACQUES E., and J. KARL HEDRICK. "Robust input-output feedback linearization." International Journal of Control 57, no. 5 (May 1993): 1133–39. http://dx.doi.org/10.1080/00207179308934435.

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2

Marquez-Martinez, L. A., and C. H. Moog. "Input–Output Feedback Linearization of Time-Delay Systems." IEEE Transactions on Automatic Control 49, no. 5 (May 2004): 781–86. http://dx.doi.org/10.1109/tac.2004.825978.

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3

Abdelhamid, Senhaji, Abdelouhab Mostafa, Attar Abdelilah, Amri Lahcen, and Bouchnaif Jamal. "Input-output Feedback Linearization Control for SM-PMSM." E3S Web of Conferences 469 (2023): 00062. http://dx.doi.org/10.1051/e3sconf/202346900062.

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This paper introduces a velocity control strategy for Surface-Mounted Permanent Magnet Synchronous Motors SM-PMSM using exact linearization and input-output decoupling techniques, which are rooted in the principles of differential geometry. The primary aim of this control approach is to establish a static state feedback mechanism and to convert the nonlinear PMSM model into a linear, decoupled, and controllable system. Initially, the state model that represents the PMSM dynamics within the d-q reference frame is defined. Subsequently, the process of designing the control through linearization and input-output decoupling is outlined. Lastly, the synthesis of the compensator is grounded in the pole placement method, aiming to drive the direct current towards zero and ensure optimal torque operation. Simulation outcomes conducted on Matlab/Simulink demonstrate the efficacy of the speed control strategy, which is facilitated by a straightforward algorithm for practical implementation. However, it is inadequate against variations in machine parameters and load torque disturbances.

4

Wang, D., and M. Vidyasagar. "Control of a Class of Manipulators With a Single Flexible Link: Part I—Feedback Linearization." Journal of Dynamic Systems, Measurement, and Control 113, no. 4 (December 1, 1991): 655–61. http://dx.doi.org/10.1115/1.2896471.

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The subject of this paper is the feedback linearization of the input-output and input-state equations for a class of multi-link, three degrees-of-freedom manipulators with the last link flexible. This class includes the 5-bar-linkage and the elbow manipulator. It is shown that the input-output equations are only feedback linearizable if the output variables are chosen appropriately. However, the nonlinear dynamics made unobservable by this feedback are not asymptotically stable which is a severe drawback. It is then shown that the input-state equations are not feedback linearizable. These results indicate that feedback linearization techniques are not appropriate for this class of manipulators. Thus, alternate methodologies should be explored. That issue is tackled in Part II.

5

Balasubramhanya, Lalitha S., and Francis J. Doyle. "The effect of multiplicative input uncertainty on input-output feedback linearization." IFAC Proceedings Volumes 32, no. 2 (July 1999): 2233–38. http://dx.doi.org/10.1016/s1474-6670(17)56379-x.

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6

Kaldmäe, Arvo, and Ülle Kotta. "Input–output linearization of discrete-time systems by dynamic output feedback." European Journal of Control 20, no. 2 (March 2014): 73–78. http://dx.doi.org/10.1016/j.ejcon.2013.12.004.

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7

Kravaris, Costas, and Chang-Bock Chung. "Nonlinear state feedback synthesis by global input/output linearization." AIChE Journal 33, no. 4 (April 1987): 592–603. http://dx.doi.org/10.1002/aic.690330408.

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8

MENDAZ, KHEIRA, and MOHAMED FLITTI. "INPUT-OUTPUT LINEARIZATION CONTROL BASED ON THE SLIDING MODE OF THE SQUIRREL CAGE MOTOR." REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE 68, no. 2 (July 3, 2023): 176–81. http://dx.doi.org/10.59277/rrst-ee.2023.68.2.10.

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Speed squirrel cage motor control is an area of research that has been in evidence for some time. In this paper, a nonlinear controller is presented for the squirrel cage motor drives, based on a combination between input-output feedback linearization control (IOLC) technique and sliding mode control (SMC) to create a new control which is sliding input-output linearization (SIOLC) control of squirrel cage motors, where the sliding mode control is used for controlling the speed of squirrel cage motor and the input-output linearization control applied for two input witch are flux and current. To test the robustness and performance of sliding input-output linearization control (SIOLC) we created a variety of internal and external parameters of the motor. The simulation results are done using Matlab/Simulink, which shows the robustness of the sliding input-output linearization control of squirrel cage motor responses.

9

Brzózka, Jerzy. "Design and Analysis of Model Following Control Structure with Nonlinear Plant." Solid State Phenomena 180 (November 2011): 3–10. http://dx.doi.org/10.4028/www.scientific.net/ssp.180.3.

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Abstract. Linearization methods of the object: input-state and input-output linearization are used usually in a standard feedback control system. However, these systems are sensitive to the changes of nonlinear characteristics of the plant. These changes can be compensated in two types of control systems: in the model following control (MFC) and adaptive. The article presents the first solution and contains: miscellaneous structures of linear control systems with model following, brief description of the linearization’s methods, simulation example of the course control of vessel and the advantages of this solution.

10

Zhou, Kai, Min Ai, Dongyang Sun, Ningzhi Jin, and Xiaogang Wu. "Field Weakening Operation Control Strategies of PMSM Based on Feedback Linearization." Energies 12, no. 23 (November 28, 2019): 4526. http://dx.doi.org/10.3390/en12234526.

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Based on current research into the mathematical model of the permanent magnet synchronous motor (PMSM) and the feedback linearization theory, a control strategy established upon feedback linearization is proposed. The Lie differential operation is performed on the output variable to obtain the state feedback of the nonlinear system, and the dynamic characteristics of the original system are transformed into linear dynamic characteristics. A current controller based on the input–output feedback linearization algorithm is designed to realize the input–output linearization control of the PMSM. The current controller decouples the d–q axis current from the flux linkage information of the motor and outputs a control voltage. When the motor speed reaches above the base speed, the field-forward and straight-axis current components are newly distributed to achieve field weakening control, which can realize the smooth transition between the constant torque region and weak magnetic region. Simulation and experimental results show the feasibility and viability of the strategy.

11

Różowicz, Sebastian, and Andrzej Zawadzki. "Input-Output Transformation Using the Feedback of Nonlinear Electrical Circuits: Algorithms and Linearization Examples." Mathematical Problems in Engineering 2018 (November 6, 2018): 1–13. http://dx.doi.org/10.1155/2018/9405256.

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This paper addresses the problem of nonlinear electrical circuit input-output linearization. The transformation algorithms for linearization of nonlinear system through changing coordinates (local diffeomorphism) with the use of closed feedback loop together with the conditions necessary for linearization are presented. The linearization stages and the results of numerical simulations are discussed.

12

Haidar, Ihab, Florentina Nicolau, Jean-Pierre Barbot, and Woihida Aggoune. "Input–output linearization of non-linear time-varying delay systems: the single-input single-output case." IMA Journal of Mathematical Control and Information 37, no. 3 (November 14, 2019): 831–54. http://dx.doi.org/10.1093/imamci/dnz030.

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Abstract This paper deals with the input–output linearization of non-linear time-varying delay systems. We introduce an extension of the Lie derivative for time-varying delay systems and derive sufficient conditions for the existence of a causal and bounded non-linear feedback linearizing the input–output behaviour of the system. Sufficient conditions ensuring the internal stability after output stabilization are also presented. Finally, several examples illustrating our main results are discussed.

13

Kheira, Mendaz, Benhadda Yamina, and Bounoua Houria. "Effect of defective NPC three level inverter on nonlinear command of induction motor." Serbian Journal of Electrical Engineering 19, no. 2 (2022): 167–92. http://dx.doi.org/10.2298/sjee2202167k.

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Speed Induction Motor (IM) control is an area of research that has been in evidence for some time now. In this paper, a nonlinear controller is presented for the induction motor drives. The nonlinear controller is designed based on an input-output feedback linearization control technique. The input-output feedback linearization control decouples the flux from the speed control and makes the synthesis of linear controllers possible. This article presented input-output linearization control of the induction motor associated with NPC three level inverter defective, the inverter faults are usually caused by operating faults in the switch elements. Switching defects occur in rectifier diodes, the capacitor and inverter IGBT switches. The inverter switches defected reduce the performance of the motor, in our study. We applied the input-output linearization control to test their robustness and performance for detection of fault influence on the physical parameters of the motor, for this purpose, we applied two faults, we started by creating a fault in two switches K1 and K7 which are in the first and second arm of the inverter. Then we created a fault in the three switches K1, K7 and K10 which are in the three arms of the inverter. The simulation results are done by the use of Matlab/Simulink that show the detection, fault effect on input-output linearization control of the different induction motor responses.

14

MENDAZ, Kheira, Mohamed FLITTI, Yamina BENHADDA, Amine ATTOU, and Abdelber BENDAOUD. "Effect of Defective Five Levels Inverter on Input Output Linearization Control for Induction Motor." Electrotehnica, Electronica, Automatica 70, no. 4 (November 15, 2022): 30–45. http://dx.doi.org/10.46904/eea.22.70.4.1108004.

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Induction Motor (IM) speed control is an area of research that has been in prominence for some time now. In this paper, a nonlinear controller is presented for induction motor drives. The nonlinear controller is designed based on input-output feedback linearization control technique. The input-output feedback linearization control decouples the flux control from the speed control and makes the synthesis of linear controllers possible. This article presented input output linearization control for induction motor associated with NPC three levels inverter defective, the inverter faults are usually caused by operating faults in the switch elements. Switching faults occur in rectifier diodes, the capacitor and IGBT switches of the inverter. The inverter switches defected reduce the performance of the motor, in our study , we apply the input-output linearization control to test their robustness and performance for detection of fault influence on the physical parameters of the motor, for this purpose we apply two faults, we start by creating a fault in two switches K1 and K7 which have in the first and second arm of the inverter then we create a faults in the three switches K1, K7 and K10 which are in the three arms of the inverter. The simulations results are done by the use of MATLAB/Simulink that show the detection fault effect by input output linearization control on the different induction motor responses.

15

Arvanitis, K. "Input-output linearization with simultaneous decoupling by restricted state feedback." IMA Journal of Mathematical Control and Information 16, no. 1 (March 1, 1999): 1–13. http://dx.doi.org/10.1093/imamci/16.1.1.

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16

Tarn, T. J., and W. Zhan. "Input-Output Decoupling and Linearization via Restricted Static-State Feedback." IFAC Proceedings Volumes 23, no. 8 (August 1990): 287–92. http://dx.doi.org/10.1016/s1474-6670(17)51930-8.

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17

Ahmed, Aamir, Martino Ajangnay, Shamboul Mohamed, and Matthew Dunnigan. "Combined Sliding Mode Control with a Feedback Linearization for Speed Control of Induction Motor." Iraqi Journal for Electrical and Electronic Engineering 7, no. 1 (June 1, 2011): 19–24. http://dx.doi.org/10.37917/ijeee.7.1.5.

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Induction Motor (IM) speed control is an area of research that has been in prominence for some time now. In this paper, a nonlinear controller is presented for IM drives. The nonlinear controller is designed based on input-output feedback linearization control technique, combined with sliding mode control (SMC) to obtain a robust, fast and precise control of IM speed. The input-output feedback linearization control decouples the flux control from the speed control and makes the synthesis of linear controllers possible. To validate the performances of the proposed control scheme, we provided a series of simulation results and a comparative study between the performances of the proposed control strategy and those of the feedback linearization control (FLC) schemes. Simulation results show that the proposed control strategy scheme shows better performance than the FLC strategy in the face of system parameters variation.

18

Zhu, Lan Xiang, Zhen Wang, Ding Li Yu, Wei Wei Yang, Lei Gu, Li Zhe Zhang, and Qi Fan Liu. "Application of Feedback Linearization to the Controller of CSTR." Advanced Materials Research 1049-1050 (October 2014): 850–54. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.850.

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Based on input-output feedback linearization scheme using the theories of differential geometry, this paper designed a controller for the continuous stirred tank reactor system which is a typical nonlinear, multi-variables, time-varying system. First, continuously different the chosen system outputs until control input appear in the expression. Then, overall linearization can be realized by input variable-substitution if some conditions are satisfied. At last, mature linear control theory is used to control the sub linear system stable. Simulation results show that the proposed control scheme is efficient and the system contains good static, dynamic performance.

19

Ghozlane, Wafa, and Jilani Knani. "NonLinear Control via Input-Output Feedback Linearization of a Robot Manipulator." Advances in Science, Technology and Engineering Systems Journal 3, no. 5 (2018): 374–81. http://dx.doi.org/10.25046/aj030543.

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20

Guemghar, K., B. Srinivasan, and D. Bonvin. "CONTROL OF PENDUBOT USING INPUT-OUTPUT FEEDBACK LINEARIZATION AND PREDICTIVE CONTROL." IFAC Proceedings Volumes 38, no. 1 (2005): 907–12. http://dx.doi.org/10.3182/20050703-6-cz-1902.00807.

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21

Isidori, A., and A. Ruberti. "A Relation Between Different Approaches to Input–Output Linearization via Feedback." Journal of the Franklin Institute 320, no. 6 (December 1985): 345–50. http://dx.doi.org/10.1016/0016-0032(85)90035-3.

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22

Bidram, Ali, Frank L. Lewis, and Ali Davoudi. "Synchronization of nonlinear heterogeneous cooperative systems using input–output feedback linearization." Automatica 50, no. 10 (October 2014): 2578–85. http://dx.doi.org/10.1016/j.automatica.2014.08.016.

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23

KIM, DONG-IL, IN-JOONG HA, and MYOUNG-SAM KO. "Control of induction motors via feedback linearization with input-output decoupling." International Journal of Control 51, no. 4 (January 1990): 863–83. http://dx.doi.org/10.1080/00207179008934102.

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24

Sun, Yipu, Xin Chen, Wenpeng He, Ziying Zhang, Edwardo F. Fukushima, and Jinhua She. "Q-learning based model-free input-output feedback linearization control method⋆." IFAC-PapersOnLine 56, no. 2 (2023): 9534–39. http://dx.doi.org/10.1016/j.ifacol.2023.10.253.

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25

Jeong, Min-Gil, and Ho-Lim Choi. "Switching Control of Electromagnetic Levitation System based on Jacobian Linearization and Input-Output Feedback Linearization." Transactions of The Korean Institute of Electrical Engineers 64, no. 4 (April 1, 2015): 578–85. http://dx.doi.org/10.5370/kiee.2015.64.4.578.

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26

Kong, Xiaobing, Xiangjie Liu, and Xiuming Yao. "Convergence Guaranteed Nonlinear Constraint Model Predictive Control via I/O Linearization." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/476367.

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Constituting reliable optimal solution is a key issue for the nonlinear constrained model predictive control. Input-output feedback linearization is a popular method in nonlinear control. By using an input-output feedback linearizing controller, the original linear input constraints will change to nonlinear constraints and sometimes the constraints are state dependent. This paper presents an iterative quadratic program (IQP) routine on the continuous-time system. To guarantee its convergence, another iterative approach is incorporated. The proposed algorithm can reach a feasible solution over the entire prediction horizon. Simulation results on both a numerical example and the continuous stirred tank reactors (CSTR) demonstrate the effectiveness of the proposed method.

27

Jovanovic, Kosta, Branko Lukic, and Veljko Potkonjak. "Feedback linearization for decoupled position/stiffness control of bidirectional antagonistic drives." Facta universitatis - series: Electronics and Energetics 31, no. 1 (2018): 51–61. http://dx.doi.org/10.2298/fuee1801051j.

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To ensure safe human-robot interaction impedance robot control has arisen as one of the key challenges in robotics. This paper elaborates control of bidirectional antagonistic drives - qbmove maker pro. Due to its mechanical structure, both position and stiffness of bidirectional antagonistic drives could be controlled independently. To that end, we applied feedback linearization. Feedback linearization based approach initially decouples systems in two linear single-input-single-output subsystems: position subsystem and stiffness subsystem. The paper elaborates preconditions for feedback linearization and its implementation. The paper presents simulation results that prove the concept but points out application issues due to the complex mechanical structure of the bidirectional antagonistic drives.

28

Le, Thi-Thanh-Hoang. "Input-Output Feedback Linearization Associates with Linear Quadratic Regulator for Stabilization Control of Furuta Pendulum System." Robotica & Management 28, no. 1 (2023): 28–35. http://dx.doi.org/10.24193/rm.2023.1.4.

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Manuscript provides a key technology, namely Input-Output Feedback Linearization Associates with Linear Quadratic Regulator (for short, IOFLALQR). The objective of this research is to study the possibility of integrating two control strategies, which includes input-output feedback linearization technique (for short, IOFL) and linear quadratic regulator controller (for short, LQR), for stabilization control of Furuta pendulum system. Furuta pendulum system belongs to the group of under-actuated robot systems. In this work, structure of IOFLALQR, control implementation, comparison of IOFLALQR and conventional LQR are adequately studied and discussed. Simulation is completed in MATLAB/Simulink environment and experiment is done on real-time experimental setup. Numerical simulation and experimental results show that the IOFLALQR are implemented on Furuta pendulum successfully. Besides, results have been drawn for demonstrating IOFLALQR better than another classical method.

29

Tsirikos, A. S., and K. G. Arvanitis. "Disturbance Rejection With Simultaneous Input-Output Linearization and Decoupling Via Restricted State Feedback." Journal of Dynamic Systems, Measurement, and Control 122, no. 1 (March 5, 1997): 49–62. http://dx.doi.org/10.1115/1.482428.

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The disturbance rejection with simultaneous input-output linearization and decoupling problem of nonsquare nonlinear systems via restricted state feedback is investigated in this paper. The problem is treated on the basis of an algebraic approach whose main feature is that it reduces the determination of the admissible state feedback control laws to the solution of an algebraic and a first order partial differential systems of equations. Verifiable necessary and sufficient conditions of algebraic nature based on these systems of equations are established for the solvability of the aforementioned problem. Moreover, an explicit expression for a special admissible restricted state feedback controller is analytically derived. [S0022-0434(00)02101-8]

30

Chiou, J. C., and S. D. Wu. "Constraint Violation Stabilization Using Input-Output Feedback Linearization in Multibody Dynamic Analysis." Journal of Guidance, Control, and Dynamics 21, no. 2 (March 1998): 222–28. http://dx.doi.org/10.2514/2.4246.

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31

Hu, Jiajia, Xinmin Xu, and Kuanyi Zhu. "Arm Exoskeleton Based on Model Predictive Control with Input/Output Feedback Linearization." Journal of Medical Imaging and Health Informatics 3, no. 3 (September 1, 2013): 432–39. http://dx.doi.org/10.1166/jmihi.2013.1177.

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32

Markadeh, Arab, R. Yazdanpanah, and J. Soltani. "Input-Output Feedback Linearization Control of Induction Motor with Adaptive Backstepping Observer." EPE Journal 18, no. 2 (June 2008): 33–40. http://dx.doi.org/10.1080/09398368.2008.11463679.

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33

Djilali, L., E. N Sanchez, and M. Belkheiri. "Neural Input Output Feedback Linearization Control of a DFIG based Wind Turbine." IFAC-PapersOnLine 50, no. 1 (July 2017): 11082–87. http://dx.doi.org/10.1016/j.ifacol.2017.08.2491.

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34

Chi, Nguyen Van. "Adaptive feedback linearization control for twin rotor multiple-input multiple-output system." International Journal of Control, Automation and Systems 15, no. 3 (May 20, 2017): 1267–74. http://dx.doi.org/10.1007/s12555-015-0245-2.

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35

Rigatos, Gerasimos G., and Guilherme V. Raffo. "Input–Output Linearizing Control of the Underactuated Hovercraft Using the Derivative-Free Nonlinear Kalman Filter." Unmanned Systems 03, no. 02 (April 2015): 127–42. http://dx.doi.org/10.1142/s2301385015500089.

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The paper proposes a nonlinear control approach for the underactuated hovercraft model based on differential flatness theory and uses a new nonlinear state vector and disturbances estimation method under the name of derivative-free nonlinear Kalman filter. It is proven that the nonlinear model of the hovercraft is a differentially flat one. It is shown that this model cannot be subjected to static feedback linearization, however it admits dynamic feedback linearization which means that the system's state vector is extended by including as additional state variables the control inputs and their derivatives. Next, using the differential flatness properties it is also proven that this model can be subjected to input–output linearization and can be transformed to an equivalent canonical (Brunovsky) form. Based on this latter description the design of a state feedback controller is carried out enabling accurate maneuvering and trajectory tracking. Additional problems that are solved in the design of this feedback control scheme are the estimation of the nonmeasurable state variables in the hovercraft's model and the compensation of modeling uncertainties and external perturbations affecting the vessel. To this end, the application of the derivative-free nonlinear Kalman filter is proposed. This nonlinear filter consists of the Kalman Filter's recursion on the linearized equivalent model of the vessel and of an inverse nonlinear transformation based on the differential flatness features of the system which enables to compute estimates for the state variables of the initial nonlinear model. The redesign of the filter as a disturbance observer makes possible the estimation and compensation of additive perturbation terms affecting the hovercraft's model. The efficiency of the proposed nonlinear control and state estimation scheme is confirmed through simulation experiments.

36

Enev, Faculty of Automatics, Technical Un. "Feedback Linearization Control of the Inertia Wheel Pendulum." Cybernetics and Information Technologies 14, no. 3 (September 1, 2014): 96–109. http://dx.doi.org/10.2478/cait-2014-0036.

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Abstract In this paper, two feedback linearizing control laws for the stabilization of the Inertia Wheel Pendulum are derived: a full-state linearizing controller, generalizing the existing results in literature, with friction ignored in the description and an inputoutput linearizing control law, based on a physically motivated definition of the system output. Experiments are carried out on a laboratory test bed with significant friction in order to test and verify the suggested performance and the results are presented and discussed. The main point to be made as a consequence of the experimental evaluation is the fact that actually the asymptotic stabilization was not achieved, but rather a limit cycling behavior was observed for the full-state linearizing controller. The input-output linearizing controller was able to drive the pendulum to the origin, with the wheel speed settling at a finite value

37

Pedro, Jimoh, and Olurotimi Dahunsi. "Neural network based feedback linearization control of a servo-hydraulic vehicle suspension system." International Journal of Applied Mathematics and Computer Science 21, no. 1 (March 1, 2011): 137–47. http://dx.doi.org/10.2478/v10006-011-0010-5.

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Neural network based feedback linearization control of a servo-hydraulic vehicle suspension systemThis paper presents the design of a neural network based feedback linearization (NNFBL) controller for a two degree-of-freedom (DOF), quarter-car, servo-hydraulic vehicle suspension system. The main objective of the direct adaptive NNFBL controller is to improve the system's ride comfort and handling quality. A feedforward, multi-layer perceptron (MLP) neural network (NN) model that is well suited for control by discrete input-output linearization (NNIOL) is developed using input-output data sets obtained from mathematical model simulation. The NN model is trained using the Levenberg-Marquardt optimization algorithm. The proposed controller is compared with a constant-gain PID controller (based on the Ziegler-Nichols tuning method) during suspension travel setpoint tracking in the presence of deterministic road disturbance. Simulation results demonstrate the superior performance of the proposed direct adaptive NNFBL controller over the generic PID controller in rejecting the deterministic road disturbance. This superior performance is achieved at a much lower control cost within the stipulated constraints.

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Bouchiba, Bousmaha, Abdeldjebar Hazzab, Hachemi Glaoui, Fellah Med-Karim, Ismaïl Bousserhane, and Pierre Sicard. "Control of multi-machine using adaptive fuzzy." Serbian Journal of Electrical Engineering 8, no. 2 (2011): 111–26. http://dx.doi.org/10.2298/sjee1102111b.

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An indirect Adaptive fuzzy excitation control (IAFLC) of power systems based on multi-input-multi-output linearization technique is developed in this paper. The power system considered in this paper consists of two generators and infinite bus connected through a network of transformers and transmission lines. The fuzzy controller is constructed from fuzzy feedback linearization controller whose parameters are adjusted indirectly from the estimates of plant parameters. The adaptation law adjusts the controller parameters on-line so that the plant output tracks the reference model output. Simulation results shown that the proposed controller IAFLC, compared with a controller based on tradition linearization technique can enhance the transient stability of the power system.

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Sun, Haipeng, Xiaolin Zhang, Yingbo Wang, Shanyao Li, Changle Sun, and Tingrui Liu. "Variable Pitch Control of Wind Turbine Based on Fuzzy Feedforward and Feedback Linearization Sliding Mode." Journal of Physics: Conference Series 2173, no. 1 (January 1, 2022): 012046. http://dx.doi.org/10.1088/1742-6596/2173/1/012046.

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Abstract When the wind turbine operates above the rated wind speed, the pitch angle is usually adjusted to make the output power stable at the rated value. As the traditional linear controller is difficult to achieve better control effect for the large inertia and strong nonlinear wind power generation system, a variable pitch control method combining fuzzy feedforward and feedback linearization sliding mode is proposed in this study. Firstly, the nonlinear wind power model is globally linearized by input/output feedback linearization, and then the feedback controller is designed by combining with sliding mode control. The fuzzy feedforward controller can give the appropriate pitch angle according to the change of wind speed and realize dynamic feedforward compensation. The simulation results show that the proposed control method can make the output power of the wind turbine stable, and has better control accuracy and robustness.

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Taniguchi, Tadanari, Luka Eciolaza, and Michio Sugeno. "LUT Controller Design with Piecewise Bilinear Systems Using Estimation of Bounds for Approximation Errors." Journal of Advanced Computational Intelligence and Intelligent Informatics 17, no. 6 (November 20, 2013): 828–40. http://dx.doi.org/10.20965/jaciii.2013.p0828.

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We propose the stabilization of nonlinear control systems approximated by Piecewise Bilinear (PB) models. The approximated model is fully parametric and a Look-Up-Table (LUT) represents its controller. Input-Output (I/O) feedback linearization is applied to stabilize PB control systems. We further propose PB modeling combined with conventional feedback linearization as a very powerful tool for analyzing and synthesizing nonlinear control systems. We also propose a method for designing robust stabilization controllers taking modeling error into consideration. Examples confirm the feasibility of our proposals.

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Chi, Nguyen Van, Nguyen Hien Trung, and Nguyen Doan Phuoc. "ABOUT THE ROBUSTNESS OF ADAPTIVE FEEDBACK LINEARIZATION CONTROLLER FOR INPUT PERTURBED UNCERTAIN FULLY-ACTUATED SYSTEMS." Vietnam Journal of Science and Technology 54, no. 2 (April 12, 2016): 276. http://dx.doi.org/10.15625/0866-708x/54/2/6233.

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The paper proposes a theorem to assert the arbitrarily good robustness of the fully actuated mechanical system controlled by the adaptive feedback linearization controller. The fully actuated system to be controlled is considerately perturbed by input disturbances and contains constant uncertain parameters in its Euler-Lagrange forced model. It is shown in this paper that independent of input disturbances the adaptive feedback linearization controller with appropriately chosen parameters will drive the output of controlled systems to the desired trajectory for any arbitrary precision. The adaptive controller is applied to the two-link planar elbow arm robot with unknown mass of the end-effector of second link and input torque noises caused by the viscous friction forces and Coulomb friction terms. Simulation results show that the arbitrary precision of the tracking errors always are guaranteed.

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Payam, Farrokh. "An adaptive input-output feedback linearization controller for doubly-fed induction machine drives." Serbian Journal of Electrical Engineering 5, no. 1 (2008): 139–54. http://dx.doi.org/10.2298/sjee0801139p.

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In this paper a nonlinear controller is presented for Doubly-Fed Induction Machine (DFIM) drives. The nonlinear controller is designed based on the adaptive input-output feedback linearization control technique, using the fifth order model of induction machine in fixed stator d, q axis reference frames with stator currents and rotor flux components as state variables. The nonlinear controller can perfectly track the torque and flux reference signals in spite of stator and rotor resistance variations. Two level SVM-PWM back-to-back voltage source inverters are employed in the rotor circuit, in order to make the drive system capable of operating in the motoring and generating modes below and above the synchronous speed. Computer simulation results obtained, confirm the effectiveness and validity of the proposed control approach.

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Abdelkrim, Arwa, Khalil Jouili, and Naceur Benhadj Braiek. "Synthesis of a Switching Control Approach Based on the Input-Output Feedback Linearization." International Review of Automatic Control (IREACO) 8, no. 1 (January 31, 2015): 1. http://dx.doi.org/10.15866/ireaco.v8i1.4573.

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Van Den Boom, Ton, Miguel Ayala Botto, and José Sá Da Costa. "Robust control of dynamical systems using neural networks with input–output feedback linearization." International Journal of Control 76, no. 18 (December 2003): 1783–89. http://dx.doi.org/10.1080/00207170310001633295.

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Kennedy, D. C., D. E. Miller, and V. H. Quintana. "Excitation Control of the Synchronous Generator by Means of Input-Output Feedback Linearization." IFAC Proceedings Volumes 28, no. 26 (December 1995): 529–34. http://dx.doi.org/10.1016/s1474-6670(17)44811-7.

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46

Zhou, Wenya, Kuilong Yin, Rui Wang, and Yue-E. Wang. "Design of Attitude Control System for UAV Based on Feedback Linearization and Adaptive Control." Mathematical Problems in Engineering 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/492680.

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Attitude dynamic model of unmanned aerial vehicles (UAVs) is multi-input multioutput (MIMO), strong coupling, and nonlinear. Model uncertainties and external gust disturbances should be considered during designing the attitude control system for UAVs. In this paper, feedback linearization and model reference adaptive control (MRAC) are integrated to design the attitude control system for a fixed wing UAV. First of all, the complicated attitude dynamic model is decoupled into three single-input single-output (SISO) channels by input-output feedback linearization. Secondly, the reference models are determined, respectively, according to the performance indexes of each channel. Subsequently, the adaptive control law is obtained using MRAC theory. In order to demonstrate the performance of attitude control system, the adaptive control law and the proportional-integral-derivative (PID) control law are, respectively, used in the coupling nonlinear simulation model. Simulation results indicate that the system performance indexes including maximum overshoot, settling time (2% error range), and rise time obtained by MRAC are better than those by PID. Moreover, MRAC system has stronger robustness with respect to the model uncertainties and gust disturbance.

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Liu, Jiangang, Zhiwu Huang, Jing Wang, Jun Peng, and Weirong Liu. "Distributed Cooperative Current-Sharing Control of Parallel Chargers Using Feedback Linearization." Mathematical Problems in Engineering 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/636784.

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We propose a distributed current-sharing scheme to address the output current imbalance problem for the parallel chargers in the energy storage type light rail vehicle system. By treating the parallel chargers as a group of agents with output information sharing through communication network, the current-sharing control problem is recast as the consensus tracking problem of multiagents. To facilitate the design, input-output feedback linearization is first applied to transform the nonidentical nonlinear charging system model into the first-order integrator. Then, a general saturation function is introduced to design the cooperative current-sharing control law which can guarantee the boundedness of the proposed control. The cooperative stability of the closed-loop system under fixed and dynamic communication topologies is rigorously proved with the aid of Lyapunov function and LaSalle invariant principle. Simulation using a multicharging test system further illustrates that the output currents of parallel chargers are balanced using the proposed control.

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Rohr, Eduardo Rath, Luís Fernando Alves Pereira, and Daniel Ferreira Coutinho. "Robustness analysis of nonlinear systems subject to state feedback linearization." Sba: Controle & Automação Sociedade Brasileira de Automatica 20, no. 4 (December 2009): 482–89. http://dx.doi.org/10.1590/s0103-17592009000400003.

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This paper presents a methodology to the robust stability analysis of a class of single-input/single-output nonlinear systems subject to state feedback linearization. The proposed approach allows the analysis of systems whose nonlinearities can be represented in the rational (and polynomial) form. Through a suitable system representation, the stability conditions are described in terms of linear matrix inequalities, which is known to have a convex (numerical) solution. The method is illustrated via a numerical example.

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Park, Gyu Man, Won Jae Hwang, and Ho Lim Choi. "Adaptive State Feedback Control of Electromagnetic Levitation System for Uncertain Ball Mass." Advanced Engineering Forum 2-3 (December 2011): 1105–10. http://dx.doi.org/10.4028/www.scientific.net/aef.2-3.1105.

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For the last several decades, many results have been presented for controlling nonlinear systems that have parameter uncertainty. In this paper, we propose an adaptive state feedback controller based on input-output feedback linearization for electromagnetic levitation system(EMS) with unknown ball mass. We analytically show the regulation of the controlled electromagnetic levitation system by the proposed adaptive state feedback controller. We show the experiment results of electromagnetic levitation system and where there is uncertain ball mass.

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Wang, He Hua, Xiao He Liu, Ming Jie Ma, and Cheng Yang. "Feedback Linearization Control of Pmssm Based on Svpwm." Advanced Materials Research 591-593 (November 2012): 1655–58. http://dx.doi.org/10.4028/www.scientific.net/amr.591-593.1655.

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In this paper, according to the AC permanent magnet synchronous servo motor of the laboratory, using appropriate method to deal with servo motor makes its physical model be established. The nonlinear dynamic mathematical model of permanent magnet synchronous servo motor is established on the basis of the physical model. Based on nonlinear dynamic mathematical model of the permanent magnet synchronous servo motor, and through the coordinate transformation and state feedback, the input-output linearization is realized and the system decoupling is achieved. According to the system's linear model, a speed tracking controller is designed. The Simulink model of Svpwm is established. The control algorithm and the model of Svpwm are verified based on theMatlab7.6/Simulink & SimPowerSystems toolbox. The simulation results show that the controller designed has a very good control effect while the feedback linearization design is simple.