Sliding mode control with particle swarm optimization algorithm for a system with external disturbance

Abstract

This project focuses on the design of sliding mode control with particle swarm optimization algorithm for a system with external disturbance. The disturbance can be matched and/or mismatched. Also the matched part can be matched to part of the control inputs. Therefore, the proposed controller is developed to be applied for any of these types of disturbance. Essentially, sliding mode control provides a control law that moves the states trajectory of the system into a prespecified sliding surface and maintains the state on this surface thereafter. The main advantage of sliding mode control is that when the system is restricted in the sliding surface its dynamic is insensitive to the external disturbance that satisfies the matching condition. If the disturbance does not satisfy the matching condition it has effect on the system during the sliding mode which may affect the stability of the system. In this project, a straight forward method for sliding surface and control law design that guarantees the reaching and sliding condition are presented. Then, sliding mode control with particle swarm optimization algorithm is proposed to reduce the effect of the mismatched disturbance on the system during the sliding mode. Finally, the proposed controller is applied to a quarter car suspension system. In general, there are four important aspects must be considered in suspension system control design. These aspects are body acceleration, tire deflection, suspension travel, and hydraulic actuator limit. In this project, the strategy that is used in designing the controller is to minimize the body acceleration by maintaining the other three aspects within an acceptable limit. The simulation results show the effectiveness of the proposed controller compared to the conventional sliding mode control.