Hybrid Adaptive Control for PEMFC Gas Pressure

This paper addresses the issues of nonlinearity and coupling between anode pressure and cathode pressure in proton exchange membrane fuel cell (PEMFC) gas supply systems. A fuzzy adaptive PI decoupling control strategy with an improved advanced genetic algorithm (AGA) is proposed. This AGA s utilized to optimize the PI parameters offline, and the fuzzy adaptive algorithm s used to adjust the PI parameters dynamically online to achieve the approximate decoupling control of the PEMFC gas supply system. According to the proposed dynamic model, the PEMFC gas supply system with the fuzzy–AGA–PI decoupling control method was simulated for comparison. The simulation results demonstrate that the proposed control system can reduce the pressure difference more efficiently with the classical control method under different load changes.

Multi-frequency micro-vibration control with hybrid adaptive control algorithm

As a popular adaptive algorithm for active vibration control (AVC), filtered-x least mean square (FxLMS) algorithm sometimes fails to suppress multiple narrowband disturbance. To control multi-frequency structure vibration, parallel-form FxLMS algorithm can be employed. However, the conventional parallel-form FxLMS does not perform well in the situation of disturbance frequency mismatch and wideband measurement noise. For this issue, the majority of the improvement approaches are based on adaptive frequency estimator. It increased the computational burden of the parallel-form FxLMS algorithm. Therefore, taking the advantage of feedback control, a hybrid adaptive control for AVC is proposed in this paper. And the “posterior” residual error is adopted for better robustness. The convergence analysis of the hybrid AVC algorithm is given. Co-simulations with ADAMS and SIMULINK are implemented to verify the effectiveness in micro-vibration control system. Some comparison experiments are implemented in a micro-vibration AVC experimental system for several typical disturbances. Experimental results confirm the feasibility and effectiveness of the proposed algorithm.