Decentralized active vibration dual-mode model predictive control for smart flexible beam

Abstract In this paper, we present a decentralized Multi-Input Multi-Output (MIMO) dual-mode Model Predictive Control (MPC) strategy for active vibration control of a smart flexible beam equipped with distributed sensors and actuators for real-time monitoring and control. Traditional centralized control approaches often face challenges such as scalability issues and higher computational demands, especially in systems with many degrees of freedom. To address these limitations, we propose a decentralized control framework in which multiple local controllers operate in parallel, each focused on mitigating vibratory disturbances in a specific region of the beam. A Kalman filter is used for state estimation, supplying each controller with the necessary state information. Simulations comparing the centralized and decentralized approaches highlight the effectiveness of the proposed decentralized MPC strategy. Results indicate that the decentralized approach successfully suppresses vibratory disturbances, enhancing the stability and performance of the smart beam. Additionally, the decentralized configuration reduces computational complexity and improves scalability relative to the centralized dual-mode MPC, making it more suitable for real-time implementation in large-scale smart structures. A comparison with the traditional Linear Quadratic Gaussian (LQG) regulator and adaptive control is also presented, underscoring the advantages of the proposed method.