Disturbance observer-based dynamic optimal setting control

Abstract

This paper deals with optimal operational control problems using a novel approach where a performance index is optimized by controller design together with set-points reselection. Firstly, the operational indices are obtained by employing some optimization algorithms. The controller is then designed for each closed loop to ensure the controlled variables can track the set points in the ideal situation. Taking advantage of disturbance observers, the set-points are reselected dynamically to minimize the effect caused by unexpected noises or disturbances. In the proposed method, the controller structure or parameters are never changed no matter what kind of disturbances affect the whole system. Finally, simulations on a 3 degrees of freedom robotic arm model are given to demonstrate the effectiveness and convenience of the proposed strategy.