Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints

• Published in: IEEE transactions on cybernetics Vol. 47; no. 10; pp. 3100 - 3109
• Main Authors: Da-Peng Li, Dong-Juan Li, Yan-Jun Liu, Shaocheng Tong, Chen, C. L. Philip
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.10.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive control; Artificial neural networks; barrier Lyapunov functions (BLFs); Computer Simulation; Delay; Delays; Design parameters; Liapunov functions; MIMO; MIMO (control systems); Neural Networks (Computer); neural networks (NNs); Nonlinear control; Nonlinear Dynamics; nonlinear multiple input multiple output (MIMO) time-delay systems; Nonlinear systems; Signal Processing, Computer-Assisted; Time Factors; Time-varying systems; Tracking control
• ISSN: 2168-2267; 2168-2275
• DOI: 10.1109/TCYB.2017.2707178

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.