Model Reference Adaptive Control Based on Tracking Differentiators

The model reference adaptive control based on tracking differentiators is proposed to deal with the parameters' large-scale uncertainty of second-order systems model.It adopts two tracking differentiators to obtain respectively the differential signals of the system output and error,which can reject the high-frequency noise amplification effect.According to the mathematical model of the controlled plant,an adaptive regulator law can automatically adjust parameters of a control law.The experiments results show that the new controller can effectively compensate the parameters' uncertainty of the second-order system when the controlled plant parameters of the radar servo system vary in large range and increase the steady and dynamic precision of the servo system.Thus can guarantee the global asymptotic stability of the system.