带有时变时滞和未知死区的纯反馈系统的自适应跟踪控制
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摘要
针对一类带有时变时滞和未知死区的纯反馈非线性系统,提出一种新的自适应模糊跟踪控制方案。采用自适应反步法设计了一个虚拟控制输入信号;利用模糊逻辑近似解决了系统中的未知函数所带来的困扰;为了处理未知死区干扰,设计了一个自适应模糊控制器,使用中值定理解决纯反馈结构中设计控制器的复杂问题。该控制方案保证闭环系统所有信号半全局一致有界,与此同时,系统的跟踪误差收敛到原点的一个小邻域内。最后,仿真例子证明了方案的有效性。
For a class of pure-feedback nonlinear systems with time-varying delay and unknown dead-zone,this paper proposed a new adaptive fuzzy tracking control scheme.A virtual control input signal was first designed by using back-stepping technique.Based on a fuzzy logic system approximation,the trouble brought about by the unknown function system was settled.In order to solve the interference by the unknown dead zone,an adaptive fuzzy controller was designed.Mean-value theorem was introduced to deal with the difficulty arising from the pure-feedback structure in designing controller.This control scheme can ensure that all the semi-global signals in the closed-loop systems are uniformly bounded and the tracking error of the system can converge to a small neighborhood of the origin.The effectiveness of the proposed scheme was finally verified with simulated examples.
For a class of pure-feedback nonlinear systems with time-varying delay and unknown dead-zone,this paper proposed a new adaptive fuzzy tracking control scheme.A virtual control input signal was first designed by using back-stepping technique.Based on a fuzzy logic system approximation,the trouble brought about by the unknown function system was settled.In order to solve the interference by the unknown dead zone,an adaptive fuzzy controller was designed.Mean-value theorem was introduced to deal with the difficulty arising from the pure-feedback structure in designing controller.This control scheme can ensure that all the semi-global signals in the closed-loop systems are uniformly bounded and the tracking error of the system can converge to a small neighborhood of the origin.The effectiveness of the proposed scheme was finally verified with simulated examples.
引文
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[2]XIE X P,YUE D,PENG C.Observer design of discrete-time T-S fuzzy systems via multi-instant augmented multi-indexed matrix approach[J].Journal of Franklin Institute,2015,352(7):2899-2919.
[3]ZHANG D,SONG H,YU L.Robust fuzzy-model-based filtering for nonlinear cyber-physical systems with multiple stochastic incomplete measurements[J].IEEE Transactions on Systems,Man&Cybernetics:Systems,2017,47(8):1826-1838.
[4]LI H,WANG J,SHI P.Output-feedback based sliding mode control for fuzzy systems with actuator saturation[J].IEEE Transactions on Fuzzy Systems,2016,24(6):1282-1293.
[5]LIU J,VAZQUEZ S,WU L,et al.Extended state observer based sliding mode control for three-phase power converters[J].IEEE Transactions on Industrial Electronics,2017,64(1):22-31.
[6]WANG F,LIU Z,ZHANG Y,et al.Adaptive quantized controller design via back-stepping and stochastic small-gain approach[J].IEEE Transactions on Fuzzy Systems,2016,24(2):330-343.
[7]SI W J,ZENG W.Adaptive neural output-feedback control for nonstrict-feedback stochastic nonlinear time-delay systems with hysteresis[J].IEEE/CAA Journal of Automatica Sinica,2017(99):1-11.
[8]LIU Y,MA H.Adaptive fuzzy tracking control of nonlinear switched stochastic systems with prescribed performance and unknown control directions[J].IEEE Transactions on Systems,Man and Cybermetics Systems,2017(99):1-10.
[9]CHEN B,LIU X P,LIU K F,et al.Adaptive control for nonlinear MIMO time-delay systems based on fuzzy approximation[J].Information Sciences,2013,222(3):576-592.
[10]WANG G,WANG C L,Li L.Fully distributed low-complexity control for nonlinear strict-feedback multiagent systems with unknown dead-zone inputs[J].IEEE Transactions on Systems,Man&Cybernetics Systems,2017(99):1-11.
[11]WEI J,HU Y,SUN M.Adaptive iterative learning control for a class of nonlinear time-varying systems with unknown delays and input dead-zone[J].IEEE/CAA Journal of Automatica Sinica,2017,1(3):302-314.
[12]WANG F,LIU Z,ZHANG Y,et al.Adaptive fuzzy control for a class of stochastic pure-feedback nonlinear systems with unknown hysteresis[J].IEEE Transactions on Fuzzy Systems,2016,24(1):140-152.
[13]XIE X,YUE D,ZHANG H,et al.Control synthesis of discrete-time T-S fuzzy systems via a multi-instant homogeneous polynomial approach[J].IEEE Transactions on Cybernetics,2016,46(3):630-640.
[14]LI Y M,TONG S C,LI T.Hybrid fuzzy adaptive output feedback control design for MIMO time-varying delays uncertain nonlinear systems[J].IEEE Transactions on Fuzzy Systems,2016,24(4):841-853.
[15]LI T,LI Z,WANG D,et al.Output-feedback adaptive neural control for stochastic nonlinear time-varying delay systems with unknown control directions[J].IEEE Transactions on Neural Network Systems,2015,26(6):1188-1201.
[16]LI H,WANG L,DU H,BOULKROUNE A.Adaptive fuzzy back-stepping tracking control for strict-feedback systems with input delay[J].IEEE Transactions on Fuzzy Systems,2017,25(3):642-652.
[17]CHEN B,LIU X P,LIU K F,et al.Adaptive fuzzy tracking control of nonlinear MIMO systems with time-varying delays[J].Fuzzy Sets&Systems,2013,217:1-21.
[18]WANG L,LI H,ZHOU Q,et al.Adaptive fuzzy control for nonstrict feedback systems with unmodeled dynamics and fuzzy dead zone via output feedback[J].IEEE Transactions on Cybernetics,2017,47(9):2400-2412.
[19]LIU Z,WANG F,ZHANG Y.Adaptive visual tracking control for manipulator with actuator fuzzy dead-zone constraint and unmodeled dynamic[J].IEEE Transactions on Systems,Man&Cybernetics,2015,45(10):1301-1312.
[20]LIU Y,GAO Y,TONG S C,et al.Fuzzy approximation-based adaptive back-stepping optimal control for a class of nonlinear discrete-time systems with dead-zone[J].IEEE Transactions on Fuzzy Systems,2016,24(1):16-28.
[21]IBRIR S,XIE W,SU C.Adaptive tracking of nonlinear systems with non-symmetric dead-zone input[J].Automatica,2007,43(3):522-530.
[22]TONG S C,LI Y M.Adaptive fuzzy output feedback tracking back-stepping control of strict-feedback nonlinear systems with unknown dead zones[J].IEEE Transactions on Fuzzy Systems,2012,20(1):168-180.
[23]BOULKROUNE A,MSAAD M,FARZA M.State and output feedback fuzzy variable structure controllers for multivariable nonlinear systems subject to input nonlinearities[J].International Journal of Advanced Manufacturing Technology,2014,71(1):539-556.
[24]LIU Y J,TONG S C.Adaptive fuzzy identification and control for a class of nonlinear pure-feedback MIMO systems with unknown dead-zones[J].IEEE Transactions on Fuzzy Systems,2015,23(5):1387-1398.
[25]TONG S C,LI Y,SHI P.Observer-based adaptive fuzzy back-stepping output feedback control of uncertain MIMO purefeedback nonlinear systems[J].IEEE Transactions on Fuzzy Systems,2012,20(4):771-785.
[26]WANG H,CHEN B,LIU K F,et al.Adaptive neural tracking control for a class of nonstrict-feedback stochastic nonlinear systems with unknown backlash-like hysteresis[J].IEEE Transactions on Neural Networks&Learning Systems,2014,25(5):947-958.
[27]ZHOU Q,WANG L,WU C,et al.Adaptive fuzzy tracking control for a class of pure-feedback nonlinear systems with timevarying delay and unknown dead zone[J].Fuzzy Sets&Systems,2017,329:36-60.
[28]WANG M,CHEN B,LIU X P,et al.Adaptive fuzzy tracking control for a class of perturbed strict-feedback nonlinear timedelay systems[J].Fuzzy Sets&Systems,2008,159(8):949-967.