Multilayer neural networks-based direct adaptive control for switched nonlinear systems

✍ Scribed by Lei Yu; Shumin Fei; Fei Long; Maoqing Zhang; Jiangbo Yu

• Publisher: Elsevier Science
• Year: 2010
• Tongue: English
• Weight: 474 KB
• Volume: 74
• Category: Article
• ISSN: 0925-2312
• DOI: 10.1016/j.neucom.2010.08.024

✦ Synopsis

This paper is concerned to present a direct adaptive neural control scheme for switched nonlinear systems with unknown constant control gain. Multilayer neural networks (MNNs) are used as a tool for modeling nonlinear functions up to a small error tolerance. The adaptive updated laws have been derived from the switched multiple Lyapunov function method, also an admissible switching signal with average dwelltime technique is given. It is proved that the resulting closed-loop system is asymptotically Lyapunov stable such that the output tracking error performance is well obtained. Finally, a simulation example of two Duffing forced-oscillation systems is given to illustrate the effectiveness of the proposed control scheme.