Study on Characteristic Model based Linear Active Disturbance Rejection Controller for a Class of Nonlinear Systems

The control problem of high-order nonlinear systems has always been a research hotspot in the field of control science. Linear active disturbance rejection controller (LADRC) regards the part which is different from the canonical form as the total disturbance, and estimates and compensates in real time, which has good control performance for nonlinear systems. However, for nonlinear systems with high-order modes, it is difficult to tune the parameters of high-order LADRC. It is just that characteristic model can compress the high-order information into the time-varying parameters of the low-order model without loss of high-order information, and LADRC based on low-order characteristic model is more convenient in implementation and parameter tuning. Therefore, in this paper, a first-order characteristic model is established first for a class of nonlinear high-order systems, then forgetting factor recursive least-squares (FFRLS) algorithm is used to obtain the parameters. Finally, based on the identified parameters and the first-order characteristic model, a first-order LADRC is designed. In order to verify the performance of the proposed method, comparative simulation has been done for a class of nonlinear system. The result shows that proposed method has faster tracking ability and stronger disturbance rejection ability than PID and golden section adaptive control (GSAC).