A new novel of composite adaptive optimal control for MR damper system subjected to mixed disturbances

초록

This study presents a new hybrid optimal controller to enhance the robustness and stability of dynamic systems subjected to uncertainties and external disturbances. In the formulation of the proposed control system, the Bolza-Meyer (BM) criterion of the optimal controller is modified to meet the system variation, and the sliding-mode controller is modified to obtain the classical control property with the prescribed performance. The proposed controller also includes the H-infinity technique as a bridge for connecting the sub-controls and improving the robust performance of the system. Fuzzy neural networks are used as filters to choose the optimal values for the next calculation. Hence, many advantages of fuzzy neural networks are acquired, related to optimal control, sliding mode control, prescribed performance, and H-infinity techniques. To demonstrate these advantages, the proposed hybrid controller is applied to a vehicle seat suspension for vibration control. Simulation results show that the proposed control obtains good performances than the compared controllers. © The Institution of Engineering and Technology 2019.

키워드