Approximation-Based Adaptive Asymptotic Quantized Control of Uncertain Non-Affine Nonlinear Dynamics

• Published in: Chinese Control Conference pp. 610 - 616
• Main Authors: Wang, Ning, Wang, Ying, Wang, Xiaolin, Zhang, Fan, Li, Jie, Shi, Xiangyu, Liu, Zongcheng
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, Chinese Association of Automation 01.07.2020
• Subjects: Adaptive systems; Asymptotic tracking; input quantization; non-affine systems; Nonlinear dynamical systems; Quantization (signal); Stability analysis; Switches; switching dynamics
• ISSN: 1934-1768
• DOI: 10.23919/CCC50068.2020.9189115

This article addresses the asymptotic tracking problem for an extended class of switched non-affine nonlinear systems subject to input quantization. By contrast with the-state-of-the-art, the most advanced peculiarity of this design lies in achieving asymptotic tracking, and considering non-smooth behaviors (e.g. switching dynamics and input quantization). To pursue this, a error compensation term is designed for compensating the approximation and quantization errors. A common lyapunov function method is exploited to handle switching dynamics. Besides, the restrictive differentiable assumption on non-affine functions is removed but simply taken to be semi-bounded and continuous. It is analytically shown that the output tracking error can converge to zero asymptotically after choosing appropriate design parameters. Comparative simulations have been conducted to verify the effectiveness of the proposed methodology.