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Journal articles on the topic 'Adaptive Nonlinear Controller Design'

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Author: Grafiati

Published: 6 September 2023

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1

Chen, Bor-Sen, and Yih-Fang Chang. "Constant Turning Force Adaptive Controller Design." Journal of Engineering for Industry 111, no. 2 (May 1, 1989): 125–32. http://dx.doi.org/10.1115/1.3188741.

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In the Constant Turning Force Adaptive Control system, the cutting process is nonlinear time-varying; besides, the stability cannot be assured by classical control theory since the cutting tools usually cut a workpiece at various cutting depths. In this paper, based on the small gain theorem, we propose a new method to design a PI controller with high robustness to stabilize the force feedback control system against the nonlinear time-varying gain perturbation in the cutting process. A simple design procedure will be presented and several illustrative simulation results are given. The practical experimental results of a converted lathe with the PI controller designed with this method also show a good robustness and good reliability.

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2

Nuella, Imma, Cheng Cheng, and Min-Sen Chiu. "Adaptive PID Controller Design for Nonlinear Systems." Industrial & Engineering Chemistry Research 48, no. 10 (May 20, 2009): 4877–83. http://dx.doi.org/10.1021/ie801227d.

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3

Izumi, Kiyotaka, Keigo Watanabe, and Masatoshi Nakamura. "Design of Simple Adaptive Nonlinear Robust Controller." Transactions of the Japan Society of Mechanical Engineers Series C 61, no. 581 (1995): 85–91. http://dx.doi.org/10.1299/kikaic.61.85.

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4

Lee, Jae-kwan, and Ken-ichi Abe. "Robust Adaptive Nonlinear Controller Design for Uncertain Nonlinear Systems." IFAC Proceedings Volumes 31, no. 22 (August 1998): 339–44. http://dx.doi.org/10.1016/s1474-6670(17)35965-7.

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5

Bidikli, Baris. "An observer-based adaptive control design for the maglev system." Transactions of the Institute of Measurement and Control 42, no. 14 (June 29, 2020): 2771–86. http://dx.doi.org/10.1177/0142331220932396.

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In this study, a nonlinear adaptive controller that can be used to control a magnetic levitation (maglev) is designed. The designed controller is equipped with a nonlinear velocity observer to provide the control without measuring velocity. Its capability to adaptively compensate all parametric uncertainties during the control process is one of the main advantages of this controller. Utilizing this capability, control of the maglev system can be realized without using any knowledge about system parameters. Due to the fast convergence capability of the designed observer and the desired model dependent structure of the adaptation rules, the proposed control design provides better performance than most of the robust and adaptive controllers that have been frequently used to control maglev system. The observer dynamics are analyzed via a Lyapunov–like preliminary analysis. Then, convergence of the observation and the tracking errors under the closed–loop operation and stability of the closed–loop error dynamics are proven via a Lyapunov–based stability analysis where the result obtained in the mentioned preliminary analysis is used. Performance of the designed observer–controller couple is demonstrated via experimental results. The efficiency of the designed controller is tested against a robust proportional–integral–derivative (PID) controller and an another Lyapunov–based nonlinear robust controller called as robust integral of sign of error (RISE) controller. Experimental results show that the designed controller performs the best tracking performance with the least control effort among these three controllers.

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6

Lou, Xiao Chun. "Adaptive Controller Design for a Class of Discrete Nonlinear Systems." Applied Mechanics and Materials 182-183 (June 2012): 1260–64. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1260.

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In this paper, we have discussed the adaptive controller problem for a class of nonlinear discrete systems. Firstly, the general nonlinear discrete-time system is transformed into a new form which is more suitable for adaptive controller design. Based on the new model, the observer is proposed to estimate the unavailable states. The adaptive controller is designed to track the desired trajectory.

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7

Zhou, Di, Tielong Shen, and Katsutoshi Tamura. "Adaptive Nonlinear Synchronization Control of Twin-Gyro Precession." Journal of Dynamic Systems, Measurement, and Control 128, no. 3 (September 12, 2005): 592–99. http://dx.doi.org/10.1115/1.2232683.

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The slewing motion of a truss arm driven by a V-gimbaled control-moment gyro is studied. The V-gimbaled control-moment gyro consists of a pair of gyros that must precess synchronously. For open-loop slewing motion control, the controller design problem is simplified into finding a feedback controller to steer the two gyros to synchronously track a specific command. To improve the synchronization performance, the integral of synchronization error is introduced into the design as an additional state variable. Based on the second method of Lyapunov, an adaptive nonlinear feedback controller is designed. For more accurate but complicated closed-loop slewing motion control, the feedback linearization technique is utilized to partially linearize the nonlinear nominal model, where two specific output functions are chosen to satisfy the system tracking and synchronization requirements. The system tracking dynamics are bounded by properly determining system indices and command signals. For the partially linearized system, the backstepping tuning function design approach is employed to design an adaptive nonlinear controller. The dynamic order of the adaptive controller is reduced to its minimum. The performance of the proposed controllers is verified by simulation.

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8

Nath, Nitendra, Irfan Kil, Ugur Hasirci, Richard E. Groff, and Timothy C. Burg. "Nonlinear Adaptive Optimal Controller Design for Anti-Angiogenic Tumor Treatment." Biomedicines 11, no. 2 (February 8, 2023): 497. http://dx.doi.org/10.3390/biomedicines11020497.

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Angiogenesis is an important process in tumor growth as it represents the regime when the tumor recruits blood vessels from the surrounding tissue to support further tumor growth. Anti-angiogenic treatments aim to shrink the tumor by interrupting the vascularization of the tumor; however, the anti-angiogenic agents are costly and the tumor response to these agents is nonlinear. Simple dosing schemes, e.g., a constant dose, may yield higher cost or lower efficacy than an approach that considers the tumor system dynamics. Hence, in this study, the administration of anti-angiogenic treatment is considered as a nonlinear control problem. The main aim of the controller design is to optimize the anti-angiogenic tumor therapy, specifically, to minimize the tumor volume and drug dose. Toward this aim, two nonlinear optimal controllers are presented. The first controller ensures exponential tracking of a desired, optimal tumor volume profile under the assumption that all parameters in the system model are known. The second controller, on the other hand, assumes all the parameters are unknown and provides asymptotic tracking. Both controllers take pharmacokinetics and pharmacodynamics into account, as well as the carrying capacity of the vascular network. Lyapunov based arguments are used to design the controllers, using stability arguments, and numerical simulation results are presented to demonstrate the effectiveness of the proposed method.

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9

Tan, Yaolong, and Ioannis Kanellakopoulos. "Adaptive nonlinear observer/controller design for uncertain nonlinear systems 1." IFAC Proceedings Volumes 32, no. 2 (July 1999): 2363–68. http://dx.doi.org/10.1016/s1474-6670(17)56401-0.

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10

Amini, Samaneh. "Adaptive Sliding Mode Controller Design For Attitude Small UAV." IAES International Journal of Robotics and Automation (IJRA) 4, no. 3 (September 1, 2015): 219. http://dx.doi.org/10.11591/ijra.v4i3.pp219-229.

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The dynamic of Unmanned Aerial Vehicle (UAV) is nonlinear, strongly coupled, multi-input multi-output (MIMO), and subject to uncertainties and external disturbances. In this paper, an adaptive sliding mode controller (ASMC) is integrated to design the attitude control system for an inner loop fixed wing UAV. In the proposed scheme, sliding mode control law parameters due to uncertainty are assumed to be unknown and are estimated via adaptation laws. The synthesis of the adaptation laws is based on the positivity and Lyapunov design principle. Navigation outer loop parameters are regulated via PID controllers. Simulation results indicate that the proposed controller design can stabilize the nonlinear system, and it is robust to parametric model uncertainties and external disturbance.

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11

Cheng, C., and M. S. Chiu. "Adaptive IMC Controller Design for Nonlinear Process Control." Chemical Engineering Research and Design 85, no. 2 (January 2007): 234–44. http://dx.doi.org/10.1205/cherd06071.

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12

Yan, Rui, ZhaoYang Dong, T. K. Saha, and Rajat Majumder. "A power system nonlinear adaptive decentralized controller design." Automatica 46, no. 2 (February 2010): 330–36. http://dx.doi.org/10.1016/j.automatica.2009.10.020.

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13

SABAH, Noor, Ekhlas HAMEED, and Muayed S. AL-HUSEINY. "OPTIMAL SLIDING MODE CONTROLLER DESIGN BASED ON WHALE OPTIMIZATION ALGORITHM FOR LOWER LIMB REHABILITATION ROBOT." Applied Computer Science 17, no. 3 (September 30, 2021): 47–59. http://dx.doi.org/10.35784/acs-2021-20.

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The Sliding Mode Controllers (SMCs) are considered among the most common stabilizer and controllers used with robotic systems due to their robust nonlinear scheme designed to control nonlinear systems. SMCs are insensitive to external disturbance and system parameters variations. Although the SMC is an adaptive and model-based controller, some of its values need to be determined precisely. In this paper, an Optimal Sliding Mode Controller (OSMC) is suggested based on Whale Optimization Algorithm (WOA) to control a two-link lower limb rehabilitation robot. This controller has two parts, the equivalent part, and the supervisory controller part. The stability assurance of the controlled rehabilitation robot is analyzed based on Lyapunov stability. The WO algorithm is used to determine optimal parameters for the suggested SMC. Simulation results of two tested trajectories (linear step signal and nonlinear sine signal) demonstrate the effectiveness of the suggested OSMC with fast response, very small overshoot, and minimum steady-state error.

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14

Bououden, S., M. Chadli, and H. R. Karimi. "Fuzzy Sliding Mode Controller Design Using Takagi-Sugeno Modelled Nonlinear Systems." Mathematical Problems in Engineering 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/734094.

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Adaptive fuzzy sliding mode controller for a class of uncertain nonlinear systems is proposed in this paper. The unknown system dynamics and upper bounds of the minimum approximation errors are adaptively updated with stabilizing adaptive laws. The closed-loop system driven by the proposed controllers is shown to be stable with all the adaptation parameters being bounded. The performance and stability of the proposed control system are achieved analytically using the Lyapunov stability theory. Simulations show that the proposed controller performs well and exhibits good performance.

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15

Zong, Xiao Ping, Miao Zhang, and Pei Guang Wang. "Adaptive Controller Design for SISO Switched Nonlinear Systems with Linear Uncertain Parameters." Applied Mechanics and Materials 602-605 (August 2014): 1362–66. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.1362.

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This paper presents that single input single output (SISO) switched nonlinear system tracks the variation of the state error to approach the excepted values by using model reference adaptive control (MRAC) method. In order to improve the adaptive control for nonlinear systems by Using Narendra method and dividing the system into two parts: linear and nonlinear parts. The controllers are designed to guarantee that the systems are closed to the model reference system with the arbitrary switching signal. Switching systems can ensure choose the best controller so that can enhance the performance. The adaptive laws are given that are based on a class of feedback single input single output nonlinear uncertain systems which can switch feedback linear standard models. The adaptive laws are different from the classic adaptive laws, because they vary with different switching signals until the best matching one comes. Simulation results show that the proposed method is effective.

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16

Guo, Yufei, Leru Luo, and Changchun Bao. "Design of a Fixed-Wing UAV Controller Combined Fuzzy Adaptive Method and Sliding Mode Control." Mathematical Problems in Engineering 2022 (January 31, 2022): 1–22. http://dx.doi.org/10.1155/2022/2812671.

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To overcome the complexity of the coupled nonlinear model of a fixed-wing UAV system and the uncertainty caused by a large number of interference factors, a control algorithm combining fuzzy adaptive control and sliding mode variable structure control was proposed. The controller algorithm mainly relies on the sliding mode variable structure control method to solve the control problem of the strongly coupled complex nonlinear system. Based on sliding mode control, a fuzzy adaptive method is introduced to reduce the chattering problem of the traditional sliding mode control, and the uncertain parameters and unknown functions caused by external disturbances are approximated by this method. In this study, two types of fuzzy adaptive sliding mode controller were designed according to the different object ranges of the fuzzy adaptive algorithm. In addition, the stability of the controllers was verified using the Lyapunov method. Finally, numerical simulations are performed to demonstrate the effectiveness of the proposed controllers by comparing with the traditional sliding mode controller.

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17

Tsai, Zhi-Ren, and Yau-Zen Chang. "Adaptive MIMO Supervisory Control Design Using Modeling Error." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/645168.

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This paper proposes an adaptive control scheme for nonlinear systems with significant nonminimum phase dynamics. The scheme is composed of an inner-level adaptive fuzzy PD control law and an outer-level supervisory control law. Importantly, the inner-level controller of the two-level scheme is designed based on a fuzzy model, which takes nonminimum phase phenomenon and modeling error explicitly into account. The scheme is both much simpler in design and more applicable to general nonlinear systems when compared with most existing nonlinear controllers. Effectiveness of the proposed control strategy is demonstrated by numerical simulation of the control of a five-degree-of-freedom aircraft system in the face of bursting disturbances.

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18

Seyedipour, Seyed Hamed, Mohsen Fathi Jegarkandi, and Saeed Shamaghdari. "Nonlinear integrated guidance and control based on adaptive backstepping scheme." Aircraft Engineering and Aerospace Technology 89, no. 3 (May 2, 2017): 415–24. http://dx.doi.org/10.1108/aeat-12-2014-0209.

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Purpose The purpose of this paper is to design an adaptive nonlinear controller for a nonlinear system of integrated guidance and control. Design/methodology/approach A nonlinear integrated guidance and control approach is applied to a homing, tail-controlled air vehicle. Adaptive backstepping controller technique is used to deal with the problem, and the Lyapanov theory is used in the stability analysis of the nonlinear system. A nonlinear model of normal force coefficient is obtained from an existing nonlinear model of lift coefficient which was validated by open loop response. The simulation was performed in the pitch plane to prove the benefits of the proposed scheme; however, it can be readily extended to all the three axes. Findings Monte Carlo simulations indicate that using nonlinear adaptive backstepping formulation meaningfully improves the performance of the system, while it ensures stability of a nonlinear system. Practical implications The proposed method could be used to obtain better performance of hit to kill accuracy without the expense of control effort. Originality/value A nonlinear adaptive backstepping controller for nonlinear aerodynamic air vehicle is designed and guaranteed to be stable which is a novel-based approach to the integrated guidance and control. This method makes noticeable performance improvement, and it can be used with hit to kill accuracy.

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19

Wang, Wei Jie, Yuan Ren, and Yi Yong Li. "Nonlinear Back Stepping Adaptive Controller Design for Spacecraft Attitude Maneuver." Applied Mechanics and Materials 574 (July 2014): 539–45. http://dx.doi.org/10.4028/www.scientific.net/amm.574.539.

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The nonlinear backstepping adaptive controller is designed for the large angle fast attitude maneuver of spacecraft with uncertainties in the moment of inertia. Deviation between the actual position and command position is depicted by error quaternion. The nonlinear backstepping tracking function is employed to design the adaptive controller both of command torque and estimation of unknown moment inertia. And the stability is analyzed based on Lyapunovo function. By Matlab/Simulink programming, the simulation of spacecraft attitude manoeuver control is discussed, and its results demonstrate the effectiveness and feasibility of the proposed controller.

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20

Zhu, Rusong, Guofu Yin, Zhenhua Chen, Shuangxi Zhang, and Zili Guo. "Temperature control of cryogenic wind tunnel with a modified L1 adaptive output feedback control." Measurement and Control 51, no. 9-10 (November 2018): 498–513. http://dx.doi.org/10.1177/0020294018808672.

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Background: Temperature is one of the main variables need to be regulated in cryogenic wind tunnel to realize the true flight Reynolds number. A new control methodology based on L1 output feedback adaptive control is deployed in the temperature control. Methods: This design is composed of three parts: linear quadratic Gaussian baseline control, L1 adaptive control and nonlinear feedforward control. A linear quadratic Gaussian controller is implemented as the baseline controller to provide the basic robustness of temperature control. A L1 output feedback adaptive controller with a modified piecewise constant adaptive law is deployed as an augmentation for the baseline controller to cancel the uncertainties within the actuator’s bandwidth. The modified adaptive law can guarantee better steady-state tracking performance compared with the standard adaptive law. A global nonlinear optimization process is carried out to obtain a suboptimal filter design for the L1 controller to maximize the performance index. The nonlinear feedforward control is to cancel the coupling effects in control of the tunnel. Results: With these design techniques, the augmented L1 adaptive controller improves the performance of the baseline controller in the presence of uncertainties of dynamics. The simulation results and analysis demonstrate the effectiveness of the proposed control architecture. Conclusion: The modification of adaptive law plus the global nonlinear optimization of the filter in the L1 adaptive control architecture helps the controller achieve good control performance and acceptable robustness for the temperature control over a wide range of operations.

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21

GE, S. S., and C. WANG. "UNCERTAIN CHAOTIC SYSTEM CONTROL VIA ADAPTIVE NEURAL DESIGN." International Journal of Bifurcation and Chaos 12, no. 05 (May 2002): 1097–109. http://dx.doi.org/10.1142/s0218127402004930.

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Though chaotic behaviors are exhibited in many simple nonlinear models, physical chaotic systems are much more complex and contain many types of uncertainties. This paper presents a robust adaptive neural control scheme for a class of uncertain chaotic systems in the disturbed strict-feedback form, with both unknown nonlinearities and uncertain disturbances. To cope with the two types of uncertainties, we combine backstepping methodology with adaptive neural design and nonlinear damping techniques. A smooth singularity-free adaptive neural controller is presented, where nonlinear damping terms are used to counteract the disturbances. The differentiability problem in controlling the disturbed strict-feedback system is solved without employing norm operation, which is usually used in robust control design. The proposed controllers can be applied to a large class of uncertain chaotic systems in practical situations. Simulation studies are conducted to verify the effectiveness of the scheme.

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22

Gao, Zi Lin, Yong Pan, Jiang Xiong, and Jin Peng Chen. "Output Stable Control Design for a Class of Nonlinear Systems Based on Adaptive Fuzzy Logic Systems." Advanced Materials Research 945-949 (June 2014): 2670–75. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2670.

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The adaptive fuzzy logic systems are constructed in this paper by utilizing the data information sampled from the inputs and outputs of unknown functions in the nonlinear systems controlled, and then output stable controller is synthesized for a class of uncertain nonlinear systems based on the universal approximation property of adaptive fuzzy logic systems. Finally, the simulation shows the validity of the method in this paper.

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23

Chen, Jie, Yan Lin, and Chang Peng Pan. "Hypersonic Aircraft Nonlinear Fault-Tolerant Controller Design." Applied Mechanics and Materials 494-495 (February 2014): 1056–59. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.1056.

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One hypersonic aircraft nonlinear observer and controller are designed synthetically to solve the part of actuator failure problem. The research model is developed based on a SISO output feedback nonlinear unobservered minimum phase system. filter is adopted to reconstruct state vectors, adaptive control law is designed to guarantee the system boundedness. Dynamic surface control is employed strategy to eliminate the explosion of terms by introducing a series of first order filters to obtain the differentiation of the virtual control inputs. Both theory analysis and simulation verification show the simpleness and effective of this method.

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24

Songa, Xin, Fang Liue, ZaoJian Zoub, Yue-Min Zhuc, JianChuan Yinb, and Feng Xub. "Nonlinear underwater robot controller design with adaptive disturbance prediction." International Journal of Computational Intelligence Systems 4, no. 4 (2011): 634. http://dx.doi.org/10.2991/ijcis.2011.4.4.19.

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25

Yang, Yongliang, Zhijie Liu, Qing Li, and Donald C. Wunsch. "Output Constrained Adaptive Controller Design for Nonlinear Saturation Systems." IEEE/CAA Journal of Automatica Sinica 8, no. 2 (February 2021): 441–54. http://dx.doi.org/10.1109/jas.2020.1003524.

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26

Lee, Dae-Sik, and Kwang Y. Lee. "DESIGN OF ADAPTIVE FUZZY CONTROLLER WITH NONLINEAR SLIDING MODE." IFAC Proceedings Volumes 35, no. 1 (2002): 151–56. http://dx.doi.org/10.3182/20020721-6-es-1901.00678.

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27

PRÖLL, THOMAS, and M. NAZMUL KARIM. "Real-time design of an adaptive nonlinear predictive controller." International Journal of Control 59, no. 3 (March 1994): 863–89. http://dx.doi.org/10.1080/00207179408923108.

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28

Cheng, Cheng, and Min-Sen Chiu. "Adaptive Single-Neuron Controller Design for Nonlinear Process Control." JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 41, no. 8 (2008): 785–95. http://dx.doi.org/10.1252/jcej.06we127.

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29

Roy, Tushar Kanti, Md Apel Mahmud, Amanullah Maung Than Oo, Md Enamul Haque, Kashem M. Muttaqi, and Nishad Mendis. "Nonlinear Adaptive Backstepping Controller Design for Islanded DC Microgrids." IEEE Transactions on Industry Applications 54, no. 3 (May 2018): 2857–73. http://dx.doi.org/10.1109/tia.2018.2800680.

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30

Pröll, T., and M. N. Karim. "Real-Time Design of an Adaptive Nonlinear Predictive Controller." IFAC Proceedings Volumes 26, no. 2 (July 1993): 887–90. http://dx.doi.org/10.1016/s1474-6670(17)48599-5.

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31

Krstic, M., and P. V. Kokotovic. "Adaptive nonlinear design with controller-identifier separation and swapping." IEEE Transactions on Automatic Control 40, no. 3 (March 1995): 426–40. http://dx.doi.org/10.1109/9.376055.

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32

Chen, Bo-Sheng, and Ching-Hung Lee. "Adaptive Model-Free Coupling Controller Design for Multi-Axis Motion Systems." Applied Sciences 10, no. 10 (May 22, 2020): 3592. http://dx.doi.org/10.3390/app10103592.

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In this study, we introduce an adaptive model-free coupling controller while using recurrent fuzzy neural network (RFNN) for multi-axis system to minimize the contour error. The proposed method can be applied to linear or nonlinear multi-axis motion control systems following desired paths. By the concept of cross-coupling control (CCC), multi-axis system is transferred into a nonlinear time-varying system due to the time-dependent coordinate transformation; tangential, normal, and bi-normal components of desired contour. Herein, we propose a model-free adaptive coupling controller design approach for multi-axis linear motor system with uncertainty and nonlinear phenomena. RFNN establishes the corresponding adaptive coupling controller to treat the uncertain system with nonlinear phenomenon. The stability of closed-loop system is guaranteed by the Lyapunov method and the adaptation of RFNN is also obtained. Simulation results are introduced in order to illustrate the effectiveness.

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Ahmadi, Karim, Davood Asadi, and Farshad Pazooki. "Nonlinear L1 adaptive control of an airplane with structural damage." Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering 233, no. 1 (September 14, 2017): 341–53. http://dx.doi.org/10.1177/0954410017730088.

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This paper investigates the design of a novel nonlinear L1 adaptive control architecture to stabilize and control an aircraft with structural damage. The airplane nonlinear model is developed considering center of gravity variation and aerodynamic changes due to damage. The new control strategy is applied by using nonlinear dynamic inversion as a baseline augmented with an L1 adaptive control strategy on NASA generic transport model in presence of un-modeled actuator dynamics, wing and vertical tail damage. The L1 adaptive controller with appropriate design of filter and gains is applied to accommodate uncertainty due to structural damage and un-modeled dynamics in the nonlinear dynamic inversion loop, and to meet desired performance requirements. The properties of the proposed nonlinear adaptive controller are investigated against a model reference adaptive control, a robust model reference adaptive control, and an adaptive sliding mode control strategy. The results clearly represent the excellent overall performance of the designed controller.

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Da, Huang, and Huang ShuCai. "Optimal controller design based on minimum principle." MATEC Web of Conferences 173 (2018): 01001. http://dx.doi.org/10.1051/matecconf/201817301001.

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Optimal control theory is the foundation of the modern control theory, the minimum principle in optimal control theory has a very important position, using the minimum principle to design an adaptive controller, the controller integration advantages of the principle of minimum is not affected by the control system of linear or nonlinear constraints, and the end state and free time, is accused of quantity can be controlled and are free to wait for a characteristic, using the minimum controller application example and simulation, the results show that the minimum principle of the designed controller has the ideal control effect.

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Song, Ki-Young, Madan M. Gupta, and Noriyasu Homma. "Design of an Error-Based Adaptive Controller for a Flexible Robot Arm Using Dynamic Pole Motion Approach." Journal of Robotics 2011 (2011): 1–9. http://dx.doi.org/10.1155/2011/726807.

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Design of an adaptive controller for complex dynamic systems is a big challenge faced by the researchers. In this paper, we introduce a novel concept ofdynamic pole motion(DPM) for the design of an error-based adaptive controller (E-BAC). The purpose of this novel design approach is to make the system response reasonably fast with no overshoot, where the system may be time varying and nonlinear with only partially known dynamics. The E-BAC is implanted in a system as a nonlinear controller with two dominant dynamic parameters: the dynamic position feedback and the dynamic velocity feedback. For illustrating the strength of this new approach, in this paper we give an example of a flexible robot with nonlinear dynamics. In the design of this feedback adaptive controller, parameters of the controller are designed as a function of the system error. The position feedbackKp(e,t)and the velocity feedbackKv(e,t)are continuously varying and formulated as a function of the system errore(t). This approach for formulating the adaptive controller yields a very fast response with no overshoot.

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Zhu, Yongliang, and Prabhakar R. Pagilla. "Adaptive Controller and Observer Design for a Class of Nonlinear Systems." Journal of Dynamic Systems, Measurement, and Control 128, no. 3 (October 18, 2005): 712–17. http://dx.doi.org/10.1115/1.2234489.

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Design of a stable adaptive controller and observer for a class of nonlinear systems that contain product of unmeasurable states and unknown parameters is considered. The nonlinear system is cast into a suitable form based on which a stable adaptive controller and observer are designed using a parameter dependent Lyapunov function. The class of nonlinear systems considered is practically relevant; mechanical systems with dynamic friction fall into this category. Experimental results on a single-link mechanical system with dynamic friction are shown for the proposed design.

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Chen, Xuemiao, Qianjin Zhao, Chunsheng Zhang, and Jian Wu. "Adaptive Asymptotic Tracking Control for a Class of Uncertain Switched Systems via Dynamic Surface Technique." Complexity 2019 (October 27, 2019): 1–9. http://dx.doi.org/10.1155/2019/9596308.

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A novel adaptive tracking control scheme is proposed for a class of uncertain nonlinear switched systems with perturbations in this paper. The common Lyapunov function method is introduced to handle the switched system in the design process of the desired adaptive controller. In addition, a dynamic surface control method is proposed by employing a nonlinear filter such that the “explosion of complexity” problem existing in the conventional backstepping design can be overcome. Under the presented adaptive controller, all the closed-loop signals are semiglobally bounded, and especially the output signal of the controlled system can follow the given reference signal asymptotically. To show the availability of the presented control scheme, a simulation is given in this paper.

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38

Niu, Yugang, James Lam, Xingyu Wang, and Daniel W. C. Ho. "Adaptive H∞ Control Using Backstepping Design and Neural Networks." Journal of Dynamic Systems, Measurement, and Control 127, no. 3 (June 24, 2004): 478–85. http://dx.doi.org/10.1115/1.1978905.

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In this paper, the adaptive H∞ control problem based on the neural network technique is studied for a class of strict-feedback nonlinear systems with mismatching nonlinear uncertainties that may not be linearly parametrized. By combining the backstepping technique with H∞ control design, an adaptive neural controller is synthesized to attenuate the effect of approximation errors and guarantee an H∞ tracking performance for the closed-loop system. In this work, the structural property of the system is utilized to synthesize the controller such that the singularity problem of the controller usually encountered in feedback linearization design is avoided. A numerical simulation illustrating the H∞ control performance of the closed-loop system is provided.

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Al-Talib, Zaidoon Sh, and Saad Fawzi AL-Azzawi. "Projective synchronization for 4D hyperchaotic system based on adaptive nonlinear control strategy." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 2 (August 1, 2020): 715. http://dx.doi.org/10.11591/ijeecs.v19.i2.pp715-722.

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<span>The main purpose of the paper is to projective synchronous chaotic oscillation in the real four-dimensional hyperchaotic model via designing many adaptive nonlinear controllers. Firstly, in view that there are many strategies in the design process of existing controllers, a nonlinear control strategy is considered as one of the important powerful tools for controlling the dynamical systems. The prominent advantage of the nonlinear controller lies in that it deals with known and unknown parameters. Then, the projective synchronize behavior of a four-dimensional hyperchaotic system is analyzed by using the Lyapunov stability theory and positive definite matrix, and the nonlinear control strategy is adopted to synchronize the hyperchaotic system. Finally, the effectiveness and robustness of the designed adaptive nonlinear controller are verified by simulation.</span>

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Chen, Zhen, Yan Mei Liu, Zhao Hui Liu, Xiao Yu Liu, and Tian Ming Song. "Intelligent Controller Design for Nonlinear Piezoelectric Smart Actuators." Applied Mechanics and Materials 635-637 (September 2014): 1447–50. http://dx.doi.org/10.4028/www.scientific.net/amm.635-637.1447.

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Nonlinear characteristic hinder the effective use of piezoelectric smart materials in sensors and actuators. In this paper, the intelligent fuzzy PID controller is designed in the Matlab-Simulink environment. The piezoelectric smart actuator model is built. An adaptive fuzzy PID control scheme was proposed. The proposed control scheme was implemented in Matlab. The results of simulation and experiment indicate that the control method has good control ability.

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Kanchanaharuthai, Adirak. "Nonlinear Adaptive Controller Design for Power Systems with STATCOM via Immersion and Invariance." ECTI Transactions on Electrical Engineering, Electronics, and Communications 14, no. 2 (May 30, 2016): 35–46. http://dx.doi.org/10.37936/ecti-eec.2016142.171133.

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In this paper, a nonlinear adaptive control of generator excitation and Static Synchronous Compensator (STATCOM) is proposed to enhance the transient stability and voltage regulation of an electrical power system. The proposed controller is designed via an adaptive immersion and invariance (I&I) methodology. In particular, a nonlinear model of the power system including two unknown constant parameters, namely an unknown damping coefficient and an unknown perturbation in mechanical power, is considered. It will be shown that the adapive I\&I control law and the parameter adaptation law proposed can accomplish the convergence of the system states to the real value of unknown parameters. Additionally, they can achieve transient stabilization along with voltage regulations. The adaptive I&I controller is validated using a simulation study on a single-machine infinite bus (SMIB) power system and compared with the standard I&I controller and an adaptive backstepping controller. Simulation results are given to indicate the effectiveness of the proposed controller for the transient stabilization and voltage regulation.

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Slama, Sabrine, Ayachi Errachdi, and Mohamed Benrejeb. "Neural Adaptive PID and Neural Indirect Adaptive Control Switch Controller for Nonlinear MIMO Systems." Mathematical Problems in Engineering 2019 (August 14, 2019): 1–11. http://dx.doi.org/10.1155/2019/7340392.

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This paper proposes an adaptive switch controller (ASC) design for the nonlinear multi-input multi-output system (MIMO). In fact, the proposed method is an online switch between the neural network adaptive PID (APID) controller and the neural network indirect adaptive controller (IAC). According to the design of the neural network IAC scheme, the adaptation law has been developed by the gradient descent (GD) method. However, the adaptive PID controller is built based on the neural network combining the PID control and explicit neural structure. The strategy of training consists of online tuning of the neural controller weights using the backpropagation algorithm to select the suitable combination of PID gains such that the error between the reference signal and the actual system output converges to zero. The stability and tracking performance of the neural network ASC, the neural network APID, and the neural network IAC are analyzed and evaluated by the Lyapunov function. Then, the controller results are compared between APID, IAC, and ASC, in this paper, applying to a nonlinear system. From simulations, the proposed adaptive switch controller has better effects both on response time and on tracking performance with smallest MSE.

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Zhu, Yong Hong, Jie Yao, and Jian Hong Wang. "NN-Based Adaptive Output Feedback Stabilization via Passivation of MIMO Uncertain System." Advanced Materials Research 588-589 (November 2012): 1527–32. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.1527.

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An NN-based output feedback stabilization problem is studied via passivation of a class of multi-input multi-output nonlinear systems with unknown nonlinear input matrix and unknown parameters. Neural networks are used to identify unknown nonlinearities, and the update laws of weight parameters are proposed. The design methods of the adaptive passive controllers for this class of systems are discussed in the paper. The corresponding adaptive passive controllers and parametric adaptive laws are designed and presented respectively. It is proved that the closed-loop system composed of the original system and the designed controller is stable by the Lyapunov method, and the controller designed can render the closed system adaptive passive. Finally, a simulation example is given to prove the effectiveness and feasibility of the proposed method.

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Sun, Liying. "Adaptive Sliding Mode Control of Generator Excitation System with Output Constraints." Mathematical Problems in Engineering 2016 (2016): 1–6. http://dx.doi.org/10.1155/2016/4247068.

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A nonlinear excitation controller for the uncertain parameters and external disturbances is designed by using the backstepping method and sliding mode control theory. In the design process, nonlinear features are retained completely with no linear technique used here. Compared with the excitation controllers designed via conventional linearization, the newly designed one has superiorities in strong robustness to external disturbances, good adaptive ability to variation of system parameters, super transient performance, and the ability to assure preset constraints. Simulation results prove the validity and stability of the controller.

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Zerroug, N., K. Behih, Z. Bouchama, and K. Zehar. "Robust Adaptive Fuzzy Control of Nonlinear Systems." Engineering, Technology & Applied Science Research 12, no. 2 (April 9, 2022): 8328–34. http://dx.doi.org/10.48084/etasr.4781.

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In this paper, an adaptive Fuzzy Fast Terminal Synergetic Controller (FFSC) for a certain class of SISO unknown nonlinear dynamic systems is proposed, that uses the concept of terminal attractor design, adaptive fuzzy synergetic control scheme, and Lyapunov synthesis approach. In contrast to the existing adaptive fuzzy synergetic control design, where the fuzzy systems are used to approximate the unknown system functions while the synergetic control guarantees robustness and achieves the asymptotic stability of the closed-loop system, in our technique both the continuous synergetic control law and the fuzzy approximator are derived to ensure finite-time convergence. Lyapunov conditions for finite-time stability and accuracy proofs in mathematics are presented to prove that the proposed adaptive scheme can achieve finite-time stable tracking of reference input and guarantee of the bonded system signals. Simulation results illustrate the design procedures and demonstrate the performance of the proposed controller.

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Cheng, Ze, Peng Xue, and Yan Li Liu. "Nonlinear Controller Design for Hypersonic Vehicles Based on Dynamic Inversion Considering Flexible States." Advanced Materials Research 424-425 (January 2012): 701–8. http://dx.doi.org/10.4028/www.scientific.net/amr.424-425.701.

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This paper describes a nonlinear adaptive dynamic inversion controller for a flexible air-breathing hypersonic vehicle model. The complete characterization of the nonlinear internal dynamic of the Bolender and Doman model with respect to velocity，altitude and angle as the regulated outputs is considered in this paper. The derivation of the internal dynamics presented in this work is comprehensive of the flexible dynamics. For the purpose of control design，we decompose the equations of motion into functional subsystems，namely，the velocity subsystem，the altitude and flight-path angle subsystem，and the angle of attack and pitch rate subsystem. Each subsystem is controlled separately using available inputs and intermediate virtual control commands. The adaptive fuzzy system is then developed to identify the uncertain in the model parameters. Simulation results are provided to demonstrate the robustness and the efficacy of the proposed controller

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Ziaei, K., and N. Sepehri. "Design of a Nonlinear Adaptive Controller for an Electrohydraulic Actuator1." Journal of Dynamic Systems, Measurement, and Control 123, no. 3 (December 1, 1998): 449–56. http://dx.doi.org/10.1115/1.1386652.

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This paper presents a new implementation of indirect model reference adaptive (MRA) control scheme for positioning of hydraulic actuators that operate by low-cost proportional valves. A proper linear discrete-time plant model is used which has dead-time and no zeros, eliminating the possibility of unstable pole-zero cancellation. The robustness of the parameter adaptation is achieved by employing the recursive least-squares algorithm in combination with a dead-zone in the adaptive law. It is shown that while the controller is adequate for hydraulic valves with linear flow characteristics, it exhibits low performance in the presence of deadband and nonlinear orifice opening characteristics of low-cost proportional valves. The linear plant model is therefore augmented by adding a static nonlinearity. The resulting nonlinear MRA controller is shown to have improved performance over its linear counterpart. Step-by-step experiments are presented to confirm the effectiveness and performance improvement of the proposed method.

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Fu, Xiao Rong. "The Design of Neuro-Fuzzy Control System Based on Data Fusion." Applied Mechanics and Materials 678 (October 2014): 406–9. http://dx.doi.org/10.4028/www.scientific.net/amm.678.406.

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An adaptive neuro-fuzzy controller of nonlinear systems is presented based on data fusion method. It reduces the input dimension of the controller using data fusion technique and simplifies the fuzzy controller’s design. The fuzzy controller was designed with self-learning of neural networks. The simulation results show that the performance of the system is superior to that using conventional fuzzy controller. It is rewarding for the research on combination of data fusion method and intelligent control technique of nonlinear systems.

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Zheng LI, and Hongbo JIN. "Fuzzy Model Reference Adaptive Controller Design for Multivariable Nonlinear System." International Journal of Digital Content Technology and its Applications 5, no. 9 (September 30, 2011): 95–103. http://dx.doi.org/10.4156/jdcta.vol5.issue9.11.

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Jiang, Nan, Xiangyong Chen, Ting Liu, Bin Liu, and Yuanwei Jing. "Nonlinear Steam Valve Adaptive Controller Design for the Power Systems." Intelligent Control and Automation 02, no. 01 (2011): 31–37. http://dx.doi.org/10.4236/ica.2011.21004.

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