Self-tuning active vibration controller using particle swarm optimization for flexible manipulator system

Abstract

This paper presents the development of an optimal self-tuning PID controller for vibration suppression of flexible manipulator structures using particle swarm optimization (PSO). A simulation environment characterizing the dynamic behavior of the flexible manipulator system was first developed using finite difference (FD) approach to acquire the input-output data of the system. The global search technique of PSO is used to estimate the model transfer function through parametric identification in comparison to the conventional recursive least square (RLS) method. Next, the control structure comprises conventional PID controller and an intelligent PID incorporated PSO controller for position and vibration control respectively acted on flexible manipulator model system. Behavior of system response including hub angle and end-point displacement are recorded and assessed. The validation of the algorithm is presented in time and frequency domains. It was demonstrated that proposed controller is effective to move the flexible link to the desired position with suppression of vibration at end-point of a flexible manipulator structure.