logo

SCIENCE CHINA Information Sciences, Volume 63 , Issue 5 : 150212(2020) https://doi.org/10.1007/s11432-019-2680-1

Adaptive event-triggered control for a class of nonlinear systemswith periodic disturbances

More info
  • ReceivedMay 14, 2019
  • AcceptedSep 16, 2019
  • PublishedMar 27, 2020

Abstract

This paper investigates the adaptive event-triggered control problem for aclass of nonlinear systems subject to periodic disturbances. To reduce thecommunication burden, a reliable relative threshold strategy is proposed.Fourier series expansion and radial basis function neural network arecombined into a function approximator to model suitable time-varyingdisturbed function of known periods in strict-feedback systems. By combiningthe Lyapunov stability theory and the backstepping technique, the proposedadaptive control approach ensures that all the signals in the closed-loopsystem are bounded, and the tracking error can be regulated to a compact setaround zero in finite time. Finally, simulation resultsare presented to verify the effectiveness of the theoretical results.


Acknowledgment

This work was partially supported by National Key R$\&$D Program of China (Grant No. 2018YFB-1700400).


References

[1] Ge S S, Wang J. Robust adaptive tracking for time-varying uncertain nonlinear systems with unknown control coefficients. IEEE Trans Automat Contr, 2003, 48: 1463-1469 CrossRef Google Scholar

[2] Song Y D, Huang X C, Wen C Y. Robust Adaptive Fault-Tolerant PID Control of MIMO Nonlinear Systems With Unknown Control Direction. IEEE Trans Ind Electron, 2017, 64: 4876-4884 CrossRef Google Scholar

[3] Xu J J, Xu L, Xie L H. Decentralized control for linear systems with multiple input channels. Sci China Inf Sci, 2019, 62: 52202 CrossRef Google Scholar

[4] Zhu Y, Zheng W X. Multiple Lyapunov Functions Analysis Approach for Discrete-Time Switched Piecewise-Affine Systems Under Dwell-Time Constraints. IEEE Transactions on Automatic Control, DOI: 10.1109/TAC.2019.2938302, 2019. Google Scholar

[5] Wei Q L, Liu D R, Lin Q. Adaptive Dynamic Programming for Discrete-Time Zero-Sum Games.. IEEE Trans Neural Netw Learning Syst, 2018, 29: 957-969 CrossRef PubMed Google Scholar

[6] Li H Y, Wang Y Y, Yao D Y. A sliding mode approach to stabilization of nonlinear Markovian jump singularly perturbed systems. Automatica, 2018, 97: 404-413 CrossRef Google Scholar

[7] Ding L, Han Q L, Wang L Y. Distributed Cooperative Optimal Control of DC Microgrids With Communication Delays. IEEE Trans Ind Inf, 2018, 14: 3924-3935 CrossRef Google Scholar

[8] Lin Z L. Control design in the presence of actuator saturation: from individual systems to multi-agent systems. Sci China Inf Sci, 2019, 62: 026201 CrossRef Google Scholar

[9] Lu Z H, Zhang L, Wang L. Controllability analysis of multi-agent systems with switching topology over finite fields. Sci China Inf Sci, 2019, 62: 12201 CrossRef Google Scholar

[10] Ren H, Karimi H R, Lu R, et al. Synchronization of Network Systems via Aperiodic Sampled-Data Control with Constant Delay and Application to Unmanned Ground Vehicles. IEEE Transactions on Industrial Electronics, DOI: 10.1109/TIE.2019.2928241, 2019. Google Scholar

[11] Zheng C, Li L, Wang L. How much information is needed in quantized nonlinear control?. Sci China Inf Sci, 2018, 61: 092205 CrossRef Google Scholar

[12] Zhang D, Han Q L, Zhang X M. Network-based modeling and proportional-integral control for direct-drive-wheel systems in wireless network environments. IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2019.2924450, 2019. Google Scholar

[13] He W, Dong Y. Adaptive Fuzzy Neural Network Control for a Constrained Robot Using Impedance Learning.. IEEE Trans Neural Netw Learning Syst, 2018, 29: 1174-1186 CrossRef PubMed Google Scholar

[14] Zhou Q, Li H Y, Wang L J. Prescribed Performance Observer-Based Adaptive Fuzzy Control for Nonstrict-Feedback Stochastic Nonlinear Systems. IEEE Trans Syst Man Cybern Syst, 2018, 48: 1747-1758 CrossRef Google Scholar

[15] Bai W W, Zhou Q, Li T S, et al. Adaptive reinforcement learning neural network control for uncertain nonlinear system with input saturation. IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2019.2921057, 2019. Google Scholar

[16] Li X M, Zhang B, Li P, et al. Finite-Horizon ${H}_\infty$ State Estimation for Periodic Neural Networks Over Fading Channels. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2019.2920368, 2019. Google Scholar

[17] Tong S C, Li Y M, Sui S. Adaptive Fuzzy Tracking Control Design for SISO Uncertain Nonstrict Feedback Nonlinear Systems. IEEE Trans Fuzzy Syst, 2016, 24: 1441-1454 CrossRef Google Scholar

[18] He W, Chen Y H, Yin Z. Adaptive Neural Network Control of an Uncertain Robot With Full-State Constraints.. IEEE Trans Cybern, 2016, 46: 620-629 CrossRef PubMed Google Scholar

[19] Zhou Q, Zhao S Y, Li H Y, et al. Adaptive neural network tracking control for robotic manipulators with dead zone. IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2018.2869375, 2018. Google Scholar

[20] Åström K J, Bernhardsson B. Comparison of periodic and event based sampling for first-order stochastic systems. In: Proceedings of the 14th IFAC World Congress, 1999. 11: 301--306. Google Scholar

[21] Arzén K E. A simple event-based. Google Scholar

[22] Zhang L C, Liang H J, Sun Y H. Adaptive Event-Triggered Fault Detection Scheme for Semi-Markovian Jump Systems With Output Quantization. IEEE Trans Syst Man Cybern Syst, 2019, : 1-12 CrossRef Google Scholar

[23] Liang H J, Zhang Z X, Ahn C K. Event-Triggered Fault Detection and Isolation of Discrete-Time Systems Based on Geometric Technique. IEEE Trans Circuits Syst II, 2019, : 1-1 CrossRef Google Scholar

[24] Cao L, Li H Y, Dong G W. Event-Triggered Control for Multiagent Systems With Sensor Faults and Input Saturation. IEEE Trans Syst Man Cybern Syst, 2019, : 1-12 CrossRef Google Scholar

[25] Heemels W P M H, Sandee J H, Van Den Bosch P P J. Analysis of event-driven controllers for linear systems. Int J Control, 2008, 81: 571-590 CrossRef Google Scholar

[26] Li Y X, Yang G H. Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.. IEEE Trans Neural Netw Learning Syst, 2018, 29: 1033-1045 CrossRef PubMed Google Scholar

[27] Ge X H, Han Q L, Wang Z D. A Dynamic Event-Triggered Transmission Scheme for Distributed Set-Membership Estimation Over Wireless Sensor Networks.. IEEE Trans Cybern, 2019, 49: 171-183 CrossRef PubMed Google Scholar

[28] Pan Y N, Yang G H. Event-triggered fuzzy control for nonlinear networked control systems. Fuzzy Sets Syst, 2017, 329: 91-107 CrossRef Google Scholar

[29] Ge X H, Han Q L. Distributed Formation Control of Networked Multi-Agent Systems Using a Dynamic Event-Triggered Communication Mechanism. IEEE Trans Ind Electron, 2017, 64: 8118-8127 CrossRef Google Scholar

[30] Liu T F, Jiang Z P. Event-Triggered Control of Nonlinear Systems with State Quantization. IEEE Trans Automat Contr, 2018, : 1-1 CrossRef Google Scholar

[31] Xing L T, Wen C Y, Liu Z T. Event-Triggered Adaptive Control for a Class of Uncertain Nonlinear Systems. IEEE Trans Automat Contr, 2017, 62: 2071-2076 CrossRef Google Scholar

[32] Xing L T, Wen C Y, Liu Z T. Event-Triggered Output Feedback Control for a Class of Uncertain Nonlinear Systems. IEEE Trans Automat Contr, 2019, 64: 290-297 CrossRef Google Scholar

[33] Chen W S. Adaptive backstepping dynamic surface control for systems with periodic disturbances using neural networks. IET Control Theor Appl, 2009, 3: 1383-1394 CrossRef Google Scholar

[34] Chen W S, Jiao L C, Li R H. Adaptive Backstepping Fuzzy Control for Nonlinearly Parameterized Systems With Periodic Disturbances. IEEE Trans Fuzzy Syst, 2010, 18: 674-685 CrossRef Google Scholar

[35] Zuo R W, Dong X M, Liu Y Z. Adaptive Neural Control for MIMO Pure-Feedback Nonlinear Systems With Periodic Disturbances.. IEEE Trans Neural Netw Learning Syst, 2019, 30: 1756-1767 CrossRef PubMed Google Scholar

[36] Ning B, Han Q L. Prescribed Finite-Time Consensus Tracking for Multiagent Systems With Nonholonomic Chained-Form Dynamics. IEEE Trans Automat Contr, 2019, 64: 1686-1693 CrossRef Google Scholar

[37] Liu Y, Liu X P, Jing Y W. Direct Adaptive Preassigned Finite-Time Control With Time-Delay and Quantized Input Using Neural Network.. IEEE Trans Neural Netw Learning Syst, 2019, : 1-10 CrossRef PubMed Google Scholar

[38] Chen W S, Wen C Y, Wu J. Global Exponential/Finite-Time Stability of Nonlinear Adaptive Switching Systems With Applications in Controlling Systems With Unknown Control Direction. IEEE Trans Automat Contr, 2018, 63: 2738-2744 CrossRef Google Scholar

[39] Li F Z, Liu Y G. Global practical tracking with prescribed transient performance for inherently nonlinear systems with extremely severe uncertainties. Sci China Inf Sci, 2019, 62: 22204 CrossRef Google Scholar

[40] Liu Y, Liu X P, Jing Y W. A Novel Finite-Time Adaptive Fuzzy Tracking Control Scheme for Nonstrict Feedback Systems. IEEE Trans Fuzzy Syst, 2019, 27: 646-658 CrossRef Google Scholar

[41] Fu J, Ma R C, Chai T Y. Global finite-time stabilization of a class of switched nonlinear systems with the powers of positive odd rational numbers. Automatica, 2015, 54: 360-373 CrossRef Google Scholar

[42] Wang F, Zhang X Y. Adaptive finite time control of nonlinear systems under time-varying actuator failures. IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2018.2868329, 2018. Google Scholar

[43] Zhao T, Liu J H, Dian S Y. Finite-time control for interval type-2 fuzzy time-delay systems with norm-bounded uncertainties and limited communication capacity. Inf Sci, 2019, 483: 153-173 CrossRef Google Scholar

[44] Ma H, Li H Y, Liang H J, et al. Adaptive fuzzy event-triggered control for stochastic nonlinear systems with full state constraints and actuator faults. IEEE Transactions on Fuzzy Systems, DOI: 10.1109/TFUZZ.2019.2896843, 2019. Google Scholar

[45] Yang Y S, Zhou C J. Robust adaptive fuzzy tracking control for a class of perturbed strict-feedback nonlinear systems via small-gain approach. Inf Sci, 2005, 170: 211-234 CrossRef Google Scholar

[46] Ahn H S, Chen Y Q. State-dependent periodic adaptive disturbance compensation. IET Control Theor Appl, 2007, 1: 1008-1014 CrossRef Google Scholar

[47] Wang F, Chen B, Liu X P. Finite-Time Adaptive Fuzzy Tracking Control Design for Nonlinear Systems. IEEE Trans Fuzzy Syst, 2018, 26: 1207-1216 CrossRef Google Scholar

[48] Park J, Sandberg I W. Universal Approximation Using Radial-Basis-Function Networks.. Neural Computation, 1991, 3: 246-257 CrossRef PubMed Google Scholar

[49] Polycarpou M M, Ioannou P A. A robust adaptive nonlinear control design. Automatica, 1996, 32: 423-427 CrossRef Google Scholar

Copyright 2020 Science China Press Co., Ltd. 《中国科学》杂志社有限责任公司 版权所有

京ICP备17057255号       京公网安备11010102003388号