Multi-agent cooperative structural vibration control of three coupled flexible beams based on value decomposition network

Abstract

Multi-coupled flexible body (MCFB) structure has the characteristics of small damping, close modes and coupled vibration, and the structural vibration is difficult to freely attenuate, which will lead to rapid fatigue failure of the structure. In order to suppress the vibration of the MCFB system quickly, a system identification scheme and a multi-agent reinforcement learning (MARL) scheme are proposed to obtain the cooperative controller. The mathematical model of the three-coupled flexible beam (TCFB) system is identified by wavelet analysis method, particle swarm optimization (PSO) and sinusoidal excitation response method. Based on value decomposition network (VDN) and deterministic policy gradient (DPG), a cooperative MARL framework is constructed to obtain the controller (VDN-DPG controller). The cooperative VDN-DPG controller is applied to the vibration control simulation and experiments of the TCFB system, and compared with proportional–derivative (PD) control without cooperation. The results show that the performance of the VDN-DPG controller is better than that of the PD controller, which verifies the effectiveness of the multi-agent cooperative control scheme based on VDN-DPG.