Optimistic Design of Auto-Disturbance Rejection Control System Based on Monte-Carlo Method

Considering a class of uncertain, state-observed, and single-variable nonlinear plants, the Monte-Carlo method is proposed for the optimization of auto-disturbance rejection control (ADRC) system. Under the premise of optimum desired dynamic equation, the extended state observer (ESO) is selected under the condition of controlled ITAE index being the optimum. Meanwhile, it has been proved that the optimized ADRC system conducts a better performance robustness and adaptability by using the Monte-Carlo method.