Adaptive NN control for nonlinear systems with uncertainty based on dynamic surface control

Neurocomputing - Tập 421 - Trang 161-172 - 2021
Zhiyong Zhou1, Dongbing Tong1, Qiaoyu Chen2,3, Wuneng Zhou3, Yuhua Xu4
1College of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
2School of Mathematics, Physics and Statistics, Shanghai University of Engineering Science, Shanghai 201620, China
3College of Information Sciences and Technology, Donghua University, Shanghai 200051, China
4School of Finance, Nanjing Audit University, Jiangsu 211815, China

Tài liệu tham khảo

Ortega, 2016, Adaptation is unnecessary in L1-adaptive control: What makes an adaptive controller “adaptive?, IEEE Control Syst. Mag., 36, 47, 10.1109/MCS.2015.2495023 Yao, 2017, Active disturbance rejection adaptive control of hydraulic servo systems, IEEE Trans. Industr. Electron., 64, 8023, 10.1109/TIE.2017.2694382 Wang, 2017, Adaptive control of robot manipulators with uncertain kinematics and dynamics, IEEE Trans. Autom. Control, 62, 948, 10.1109/TAC.2016.2575827 Hasanien, 2016, An adaptive control strategy for low voltage ride through capability enhancement of grid-connected photovoltaic power plants, IEEE Trans. Power Syst., 31, 3230, 10.1109/TPWRS.2015.2466618 Yu, 2015, Observer and command-filter-based adaptive fuzzy output feedback control of uncertain nonlinear systems, IEEE Trans. Industr. Electron., 62, 5962, 10.1109/TIE.2015.2418317 Ma, 2019, Adaptive dynamic surface control design for uncertain nonlinear strict-feedback systems with unknown control direction and disturbances, IEEE Trans. Syst. Man Cybern.: Syst., 49, 506, 10.1109/TSMC.2018.2855170 Zhai, 2020, Adaptive fuzzy fault-tolerant tracking control of uncertain nonlinear time-varying delay systems, IEEE Trans. Syst. Man Cybern.: Syst., 50, 1840, 10.1109/TSMC.2018.2789441 Liu, 2018, Adaptive fuzzy output feedback control for a class of nonlinear systems with full state constraints, IEEE Trans. Fuzzy Syst., 26, 2607, 10.1109/TFUZZ.2018.2798577 Tong, 2016, Observed-based adaptive fuzzy decentralized tracking control for switched uncertain nonlinear large-scale systems with dead zones, IEEE Trans. Syst. Man Cybern.: Syst., 46, 37, 10.1109/TSMC.2015.2426131 Tang, 2016, Robust adaptive neural tracking control for a class of perturbed uncertain nonlinear systems with state constraints, IEEE Trans. Syst. Man Cybern.: Syst., 46, 1618, 10.1109/TSMC.2015.2508962 Li, 2018, Observer-based fuzzy adaptive event-triggered control codesign for a class of uncertain nonlinear systems, IEEE Trans. Fuzzy Syst., 26, 1589, 10.1109/TFUZZ.2017.2735944 Yang, 2018, SGD-based adaptive NN control design for uncertain nonlinear systems, IEEE Trans. Neural Networks Learn. Syst., 29, 5071, 10.1109/TNNLS.2018.2790479 Tong, 2016, Adaptive fuzzy tracking control design for SISO uncertain nonstrict feedback nonlinear systems, IEEE Trans. Fuzzy Syst., 24, 1441, 10.1109/TFUZZ.2016.2540058 Wen, 2017, Adaptive neural-fuzzy sliding-mode fault-tolerant control for uncertain nonlinear systems, IEEE Trans. Syst. Man Cybern.: Syst., 47, 2268, 10.1109/TSMC.2017.2648826 Wang, 2017, Backstepping-based Lyapunov function construction using approximate dynamic programming and sum of square techniques, IEEE Trans. Cybern., 47, 3393 Wang, 2015, Adaptive fuzzy backstepping control for a class of nonlinear systems with sampled and delayed measurements, IEEE Trans. Fuzzy Syst., 23, 302, 10.1109/TFUZZ.2014.2312026 Li, 2012, Neural-adaptive output feedback control of a class of transportation vehicles based on wheeled inverted pendulum models, IEEE Trans. Control Syst. Technol., 20, 1583, 10.1109/TCST.2011.2168224 Bechlioulis, 2008, Robust adaptive control of feedback linearizable MIMO nonlinear systems with prescribed performance, IEEE Trans. Autom. Control, 53, 2090, 10.1109/TAC.2008.929402 Modares, 2013, Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks, IEEE Trans. Neural Networks Learn. Syst., 24, 1513, 10.1109/TNNLS.2013.2276571 Chen, 2016, Observer-based adaptive backstepping consensus tracking control for high-order nonlinear semi-strict-feedback multiagent systems, IEEE Trans. Cybern., 46, 1591, 10.1109/TCYB.2015.2452217 Wen, 2018, Optimized backstepping for tracking control of strict-feedback systems, IEEE Trans. Neural Networks Learn. Syst., 29, 3850, 10.1109/TNNLS.2018.2803726 Liu, 2017, Adaptive fuzzy backstepping control of fractional-order nonlinear systems, IEEE Trans. Syst. Man Cybern.: Syst., 47, 2209, 10.1109/TSMC.2016.2640950 Cai, 2017, Adaptive backstepping control for a class of nonlinear systems with non-triangular structural uncertainties, IEEE Trans. Autom. Control, 62, 5220, 10.1109/TAC.2016.2628159 Luo, 2016, Chaos analysis-based adaptive backstepping control of the microelectromechanical resonators with constrained output and uncertain time delay, IEEE Trans. Industr. Electron., 63, 6217, 10.1109/TIE.2016.2569462 Lai, 2018, Adaptive backstepping-based tracking control of a class of uncertain switched nonlinear systems, Automatica, 91, 301, 10.1016/j.automatica.2017.12.008 Xu, 2014, Composite neural dynamic surface control of a class of uncertain nonlinear systems in strict-feedback form, IEEE Trans. Cybern., 44, 2626, 10.1109/TCYB.2014.2311824 Wang, 2011, Adaptive neural control of pure-feedback nonlinear time-delay systems via dynamic surface technique, IEEE Trans. Syst. Man Cybern. Part B (Cybernetics), 41, 1681, 10.1109/TSMCB.2011.2159111 Xu, 2015, Global neural dynamic surface tracking control of strict-feedback systems with application to hypersonic flight vehicle, IEEE Trans. Neural Networks Learn. Syst., 26, 2563, 10.1109/TNNLS.2015.2456972 Xu, 2020, Exponential synchronization of chaotic systems with stochastic noise via periodically intermittent control, Int. J. Robust Nonlinear Control, 30, 2611, 10.1002/rnc.4893 Kwan, 2000, Robust backstepping control of nonlinear systems using neural networks, IEEE Trans. Syst. Man Cybern.-Part A, 30, 753, 10.1109/3468.895898 Li, 2004, Robust and adaptive backstepping control for nonlinear systems using RBF neural networks, IEEE Trans. Neural Networks, 15, 693, 10.1109/TNN.2004.826215 Tong, 2020, Sliding mode control of a class of nonlinear systems, J. Franklin Inst., 357, 1560, 10.1016/j.jfranklin.2019.11.004 Xu, 2019, Exponential stability of Markovian jumping systems via adaptive sliding mode control, IEEE Trans. Syst. Man Cybern.: Syst., 10.1109/TSMC.2018.2884565 Shi, 2018, Adaptive neural dynamic surface control for nonstrict-feedback systems with output dead zone, IEEE Trans. Neural Networks Learn. Syst., 29, 5200, 10.1109/TNNLS.2018.2793968 Fan, 2019, Design of a feedforward-feedback controller for a piezoelectric-driven mechanism to achieve high-frequency nonperiodic motion tracking, IEEE/ASME Trans. Mechatron., 24, 853, 10.1109/TMECH.2019.2899069 Song, 2017, Guest editorial special issue on new developments in neural network structures for signal processing, autonomous decision, and adaptive control, IEEE Trans. Neural Networks Learn. Syst., 28, 494, 10.1109/TNNLS.2016.2617239 Tian, 2016, Learning subspace-based RBFNN using coevolutionary algorithm for complex classification tasks, IEEE Trans. Neural Networks Learn. Syst., 27, 47, 10.1109/TNNLS.2015.2411615 Meng, 2018, Nonlinear system modeling using RBF networks for industrial application, IEEE Trans. Industr. Inf., 14, 931, 10.1109/TII.2017.2734686 Tong, 2020, Sliding mode control for nonlinear stochastic systems with Markovian jumping parameters and mode-dependent time-varying delays, Nonlinear Dyn., 100, 1343, 10.1007/s11071-020-05597-4 Raitoharju, 2016, Training radial basis function neural networks for classification via class-specific clustering, IEEE Trans. Neural Networks Learn. Syst., 27, 2458, 10.1109/TNNLS.2015.2497286 Han, 2018, An adaptive-PSO-based self-organizing RBF neural network, IEEE Trans. Neural Networks Learn. Syst., 29, 104, 10.1109/TNNLS.2016.2616413 Hwang, 2016, Recurrent-neural-network-based multivariable adaptive control for a class of nonlinear dynamic systems with time-varying delay, IEEE Trans. Neural Networks Learn. Syst., 27, 388, 10.1109/TNNLS.2015.2442437 Liu, 2017, Adaptive neural backstepping for a class of switched nonlinear system without strict-feedback form, IEEE Trans. Syst. Man Cybern.: Syst., 47, 1315, 10.1109/TSMC.2016.2585664 Niu, 2020, Multiple Lyapunov functions for adaptive neural tracking control of switched nonlinear nonlower-triangular systems, IEEE Trans. Cybern., 50, 1877, 10.1109/TCYB.2019.2906372 Niu, 2018, Adaptive control for stochastic switched nonlower triangular nonlinear systems and its application to a one-link manipulator, IEEE Trans. Syst. Man Cybern.: Syst., 48, 1701, 10.1109/TSMC.2017.2685638 Segal, 2000, Radial basis function (RBF) network adaptive power system stabilizer, IEEE Trans. Power Syst., 15, 722, 10.1109/59.867165 Xiaofang, 2010, RBF networks-based adaptive inverse model control system for electronic throttle, IEEE Trans. Control Syst. Technol., 18, 750, 10.1109/TCST.2009.2026397 Wen, 2017, Neural network-based adaptive leader-following consensus control for a class of nonlinear multiagent state-delay systems, IEEE Trans. Cybern., 47, 2151, 10.1109/TCYB.2016.2608499 Mou, 2015, Dynamic surface control using neural networks for a class of uncertain nonlinear systems with input saturation, IEEE Trans. Neural Networks Learn. Syst., 26, 2086, 10.1109/TNNLS.2014.2360933 Ge, 2004, Adaptive neural control of uncertain MIMO nonlinear systems, IEEE Trans. Neural Networks, 15, 674, 10.1109/TNN.2004.826130 Chen, 2010, Adaptive NN backstepping output-feedback control for stochastic nonlinear strict-feedback systems with time-varying delays, IEEE Trans. Syst. Man Cybern. Part B (Cybernetics), 40, 939, 10.1109/TSMCB.2009.2033808