Abstract
This article presents a novel approach that combines Kalman filtering and model predictive control (MPC) algorithms to achieve stable output in a multioutput wireless power transfer (WPT) system for automated guided vehicles (AGVs). Traditional WPT systems often struggle to maintain stable output under varying load conditions and environmental disturbances, impacting the efficiency and reliability of AGV operations. To address this issue, we introduce a Kalman filter for real-time state estimation, coupled with an MPC algorithm for system prediction and control, thereby enhancing the system's robustness and dynamic response performance. Simulation and experimental results validate the superior performance of the proposed method under various operating conditions, demonstrating significant anti-interference capability and stable output characteristics. The results indicate that this method can markedly improve the stability and reliability of the AGV WPT system, providing strong technical support for its practical application.