An Improved Multi-Level Adaptive Control Algorithm Based on Parameters Self-Tuning for a Class of SISO Nonlinear Systems

Abstract

In this paper, a multi-level adaptive control algorithm using parameters self-tuning is proposed for improving the tracking performance of a class of SISO nonlinear systems. This scheme is comprised of the pseudo partial derivative estimation law and the adaptive control law. The adaptive control law is derived from a novel higher order weighted one-step-ahead criterion function which exploits more previous control information. In order to identify the laws’ penalty factors which partly imply the dynamics of the system, an approach of parameters self-tuning is proposed with on-line recursive gradient algorithm. This design is model free and depends directly on the pseudo partial derivative updating on-line with the input and output data Simulation examples are provided to illustrate the effectiveness of the proposed method.