A Finite-Time Back-Stepping Dynamic Surface Control

doi:10.13190/j.jbupt.2018-109

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2019, Vol. 42 ›› Issue (2): 70-76.doi: 10.13190/j.jbupt.2018-109

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A Finite-Time Back-Stepping Dynamic Surface Control

LIU Yi-cheng¹, JIN Zhou¹, PU Ming²

1. College of Engineering and Information Technology, Sichuan University, Chengdu 610065, China;
2. Chengdu University of Information Technology School of Control Engineering, Chengdu 610225, China

Received:2018-05-30 Online:2019-04-28 Published:2019-04-09

Abstract

Abstract: A finite time back-stepping dynamic surface control was proposed for n-order nonlinear systems with external disturbances and modeling errors. In the subsystem controller design of the dynamic surface control method, a nonlinear filter with fast finite time convergence was designed to replace the first order linear filter. This method can avoid "explosion of terms", reduce the error accumulation of high order system, and at the same time can avoid the singularity problem that is difficult to solve in high order system of finite time control. In order to solve the problem that the estimation error was not taken into account in the stability analysis of dynamic surface control, the stability of the estimation error was considered, and the steady-state control error was given. Finally, combining with the position control of the four-rotor aircraft, the simulation verifies its engineering practicability and superiority.

Key words: finite-time, dynamic surface control, nonlinear filter, explosion of terms, estimation error

CLC Number:

TP273

LIU Yi-cheng, JIN Zhou, PU Ming. A Finite-Time Back-Stepping Dynamic Surface Control[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(2): 70-76.

References

[1] Isidori Alberto. Nonlinear control systems[M]. London:Springer Science and Business Media, 2013:91-99.
[2] Levant A. Sliding order and sliding accuracy in sliding mode control[J]. International Journal of Control, 1993, 58(6):1247-1263.
[3] Krstic M, Kanellakopoulos I, Kokotovic P V. Nonlinear and adaptive control design[M]. New York:Wiley, 1995:490-491.
[4] Ramirez-Rodriguez H, Parra-Vega V, Sanchez-Orta A, et al. Robust backstepping control based on integral sliding modes for tracking of quadrotors[J]. Journal of Intelligent and Robotic Systems, 2014, 73(1-4):51-66.
[5] Wang Y, Wilson P A, Liu X. Adaptive neural network-based backstepping fault tolerant control for underwater vehicles with thruster fault[J]. Ocean Engineering, 2015(110):15-24.
[6] Roy T K. Robust adaptive backstepping speed controller design for a series DC motor[C]//Electrical and Computer Engineering (WIECON-ECE), 2015 IEEE International WIE Conference on.[S.l.]:IEEE, 2015:243-246.
[7] Swaroop D, Hedrick J K, Yip P P, et al. Dynamic surface control for a class of nonlinear systems[J]. IEEE Transactions on Automatic Control, 2000, 45(10):1893-1899.
[8] Xu B, Shi Z, Yang C, et al. Composite neural dynamic surface control of a class of uncertain nonlinear systems in strict-feedback form[J]. IEEE Transactions on Cybernetics, 2014, 44(12):2626-2634.
[9] Chen M, Tao G, Jiang B. Dynamic surface control using neural networks for a class of uncertain nonlinear systems with input saturation[J]. IEEE Transactions on Neural Networks and Learning Systems, 2015, 26(9):2086-2097.
[10] Pan Y, Yu H. Composite learning from adaptive dynamic surface control[J]. IEEE Transactions on Automatic Control, 2016, 61(9):2603-2609.
[11] Pan Y, Yu H. Dynamic surface control via singular perturbation analysis[J]. Automatica, 2015(57):29-33.
[12] Du J, Abraham A, Yu S, et al. Adaptive dynamic surface control with Nussbaum gain for course-keeping of ships[J]. Engineering Applications of Artificial Intelligence, 2014(27):236-240.
[13] Peng Z, Wang D, Wang J. Predictor-based neural dynamic surface control for uncertain nonlinear systems in strict-feedback form[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(9):2156-2167.
[14] Wang Y, Song Y. Fraction dynamic surface based neuroadaptive finite-time containment control of multiagent systems in nonaffine pure-feedback form[J]. IEEE Transactions on Neural Networks and Learning Systems, 2017, 28(3):678-689.
[15] X Yu, M Zhihong. Fast terminal sliding-mode control design for nonlinear dynamical systems[J]. IEEE Transactions on Circuits and Systems I:Fundamental Theory and Applications, 2002, 49(2):261-264.
[16] Liu Yicheng, Ma Junhui, Tu Haiyan. Robust command filtered adaptive backstepping control for a quadrotor aircraft[J]. Journal of Control Science and Engineering, 2018:1-9.

A Finite-Time Back-Stepping Dynamic Surface Control

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