A Study of Adaptive Control Based on CMAC Neural Network: Design and Application for Unknown Nonlinear System

Over the last few years, the study in adaptive intelligent control utilizing Fuzzy, Neural Network for a class of unknown nonlinear systems has attracted considerable attention. In this book, a new hybrid adaptive cerebeller model articulation controller (CMAC) sliding mode control system is developed. The hybrid adaptive CMAC sliding mode controller (HACSMC) uses the direct and indirect adaptive CMAC controllers to perform the equivalent control of sliding mode control (SMC). Two types of methods, sign function switching controller and CMAC switching controller are proposed to design the switching control law of SMC. In addition, the adaptive laws of the control system are derived in the sense of Lyapunov theorem, so that the stability of the system can be guaranteed. Finally, the proposed control system is applied to inverted pendulum system and Chua?s chaotic circuit. The simulation results show that the HACSMC can not only make control system have good tracking performance and strong robustness but also have more flexibility during the design process.