固体氧化物燃料电池系统的鲁棒反馈模型预测控制

固体氧化物燃料电池系统工作过程中燃料与氧化剂的压力差和燃料利用率的变化值是衡量系统运行安全、稳定长效、具有较好鲁棒性的重要指标.本文提出采用离线计算、在线优化相结合的带有输出反馈的鲁棒模型预测控制方法,分别将燃料与氧化剂的压力差和燃料利用率作为输入和输出约束,离线计算目标函数上界及其系列渐近稳定域,在线时对控制量进行精确定位.仿真结果表明,采用了状态反馈的模型预测控制方法能有效克服模型失配问题并迅速获得被控量的预测值,使系统当负载电流发生波动时能克服变化引起的参数偏差,提高了响应速度,增强了系统鲁棒性.

Robust feedback model predictive control of the solid oxide fuel cell's system

In the operating process of the solid oxide fuel cell system, the pressure difference between fuel and air and the fuel utility are the important indexes, which evaluate the system's safety, long-term stability and better robustness. It is proposed in this paper that an output feedback robust model predictive control method is applied which is obtained the offline calculation and online optimal. The pressure difference between fuel and air and the fuel utility are used as input and output constraints, respectively. When offline, calculating upper bounds of the objective function and its series asymptotic stable domain, and online, making accurate position of control parameters. The simulation results show that using the state feedback model predictive control method can effectively overcome the model mismatch problem of the system and parameter deviation caused by the loaded current disturbance, improve the response speed, and enhance system robustness.