Abstract:

The generalized predictive control is proposed that based on the control strategy of microbial fuel cell, combined with the characteristics of microbial fuel cells, to investigate the problems of unstable power output in the initial operation stage and the long adjustment time during the operation of an MFC, compared with the MFC system of PID control method joined, joined generalized predictive control of MFC system output is able to avoid the response greatly jitter and fast response, good robustness and dynamic adjustment to ensure that the dynamic output curve fast and accurate tracking system settings. The model identification is carried by the least squares method with forgetting factor to get linear model as a predictive model. Then, generalized predictive control (GPC) can adjust effectively the output response of an MFC under random influent flow at constant external resistance and acetate concentration. The simulation results show that GPC can achieve a good control effect and system robustness adjustment process has also been greatly improved in terms of speed control response. Effective implementation of the optimization of dynamic performance and robust performance of microbial fuel cell system to verify the proposed algorithm is effective and feasible.

Key words: microbial fuel cell, influent flow, output response, generalized predictive control

摘要：

针对MFC系统启动阶段输出响应不稳定以及调节时间较长的问题,结合微生物燃料电池自身特性,提出了基于广义预测控制(generalized predictive control,GPC)的微生物燃料电池(microbial fuel cell,MFC)控制策略。与加入PID控制方法对比得知,加入GPC的MFC系统输出能够避免响应出现大幅度的抖动,且响应速度快,动态调节鲁棒性好,保证了动态输出曲线快速准确地跟踪系统设定值。在给定外电阻为恒值和醋酸盐浓度随时间阶梯变化时,通过带遗忘因子的最小二乘法进行模型辨识,将所得线性模型作为预测模型,采用GPC算法进行控制。仿真表明,GPC能在控制响应速度方面取得好的控制效果以及系统调节过程中的鲁棒性也有了较大的改善。有效地实现了对微生物燃料电池系统的动态性能以及鲁棒性能的优化,验证了所提出的算法有效可行。

关键词: 微生物燃料电池, 流入物流量, 输出响应, 广义预测控制