Nonlinear Adaptive Switching Control Method Based on Unmodeled Dynamics Compensation
基于未建模动态补偿的非线性自适应切换控制方法

This paper presents a nonlinear controller based on unmodeled dynamics compensation for a class of uncertain and discrete-time single-input single-output (SISO) nonlinear systems with unstable zero-dynamics. By combining an adaptive-network-based fuzzy inference system (ANFIS) with "one-to-one mapping", a compensator for unmodeled dynamics is constructed. With the above development, an adaptive switching control method is proposed that consists of a linear adaptive controller, a nonlinear adaptive controller and a switching mechanism. By using switching between the above two controllers, it has been shown that both an improved performance and stability can be achieved simultaneously. The paper assumes the unmodeled dynamics of the systems to satisfy a linear growth condition, which relaxes the widely used global boundedness condition on the unmodeled dynamics. The analysis on stability and convergence of the adaptive control method are established. Finally, through the simulation based comparative study and the experiment of the proposed control on a tank level adaptive control system, the effectiveness of the proposed method is justified.