Design of robust trackers and unknown nonlinear perturbation estimators for a class of nonlinear systems: HTRDNA algorithm for tracker optimization

Jiunn Shiou Fang, Jason Sheng Hong Tsai, Jun Juh Yan, Chang He Tzou, Shu Mei Guo

研究成果: Article


A robust linear quadratic analog tracker (LQAT) consisting of proportional-integralderivative (PID) controller, sliding mode control (SMC), and perturbation estimator is proposed for a class of nonlinear systems with unknown nonlinear perturbation and direct feed-through term. Since the derivative type (D-type) controller is very sensitive to the state varying, a new D-type controller design algorithm is developed to avoid an unreasonable large value of the controller gain. Moreover, the boundary of D-type controller is discussed. To cope with the unknown perturbation effect, SMC is utilized. Based on the fast response of SMC controlled systems, the proposed perturbation estimator can estimate unknown nonlinear perturbation and improve the tracking performance. Furthermore, in order to tune the PID controller gains in the designed tracker, the nonlinear perturbation is eliminated by the SMC-based perturbation estimator first, then a hybrid Taguchi real coded DNA (HTRDNA) algorithm is newly proposed for the PID controller optimization. Compared with traditional DNA, a new HTRDNA is developed to improve the convergence performance and effectiveness. Numerical simulations are given to demonstrate the performance of the proposed method.

出版狀態Published - 2019 十二月 1


All Science Journal Classification (ASJC) codes

  • Mathematics(all)