On-line Learning Adaptive Control Based on Linear Neuron

A novel on-line learning adaptive control scheme based on linear neuron is presented to facilitate controller design of unknown nonlinear dynamic system. Dynamic linearization method being used for control oriented model known as the linear neuron, and inputs of linear neuron are the difference operator of nonlinear system input, weighting factor of linear neuron on-line learning to dynamic approximate nonlinear system. Adaptive control law and the weighting factor on-line learning algorithm in-turn circulating to control nonlinear system, furthermore, stability analysis of closed loop system and given the relationship between static error and bounded disturbance. At last, the effectiveness of the proposed scheme is illustrated by simulation of a nonlinear dynamic systems at Matlab-Simulink platform.