Vibration suppression control of smart piezoelectric rotating truss structure by parallel neuro-fuzzy control with genetic algorithm tuning

The main goal of this paper is to develop a novel approach for vibration control on a piezoelectric rotating truss structure. This study will analyze the dynamics and control of a flexible structure system with multiple degrees of freedom, represented in this research as a clamped–free–free–free truss type plate rotated by motors. The controller has two separate feedback loops for tracking and damping, and the vibration suppression controller is independent of position tracking control. In addition to stabilizing the actual system, the proposed proportional–derivative (PD) control, based on genetic algorithm (GA) to seek the primary optimal control gain, must supplement a fuzzy control law to ensure a stable nonlinear system. This is done by using an intelligent fuzzy controller based on adaptive neuro-fuzzy inference system (ANFIS) with GA tuning to increase the efficiency of fuzzy control. The PD controller, in its assisting role, easily stabilized the linear system. The fuzzy controller rule base was then constructed based on PD performance-related knowledge. Experimental validation for such a structure demonstrates the effectiveness of the proposed controller. The broad range of problems discussed in this research will be found useful in civil, mechanical, and aerospace engineering, for flexible structures with multiple degree-of-freedom motion. ► This paper proposes a novel control methodology for multi-DOF flexible structures. ► The controller has two separate feedback loops for tracking and damping. ► The proposed PD control, based on GA to seek the primary optimal control gain. ► The fuzzy rule base was then constructed based on PD performance-related knowledge. ► The problems discussed in this research will be useful in various engineering area.