摘要
为了克服传统的预测控制在线计算量大、对模型要求高和灵活性差的缺点,使其更加适应于现代流程工业的过程控制,将分数阶PID(FOPID)算法和第三代预测控制算法预测函数算法(PFC)相结合,利用FOPID去改进PFC的性能指标函数,推导出了一种改进型的具有5个可调参数的预测函数算法。通过仿真和实时以太网(EPA)实验装置对改进型预测函数算法进行研究,结果表明该算法克服了PFC稳态性能差,对模型要求高和FOPID震荡周期长的缺点,具有静态误差小、上升速度快、超调小、调节时间短和鲁棒性强等优点。同时该算法与传统预测控制器结构类似,便于广大工程人员设计者实现。
In order to overcome the drawbacks of massive online calculation, high requirements for models, and low flexibility in traditional predictive control, and to make it more suitable for modern process industries, we combined fractional-order PID （FOPID） and third-generation predictive functional control （ PFC）, and improved performance indicators of PFC through FOPID. Finally, we derived the improved predictive functional algorithm which has 5 adjustable parameters. Through the simulation and research about the improved predictive functional algorithm on real-time Ethernet for plant automation （EPA） experimental facilities, results show this algorithm, on the one hand, overcomes the defects, namely, low steady-state performance of PFC, high requirements for models, and long oscillation period of FOPID; on the other hand, it has some merits like smaller steady-state errors, higher rate of climb, less overshoot, shorter adjustment time, stronger robustness, etc. Besides, this structure is similar to conventional predictive controller, which is convenient for engineering designers.
出处
《控制工程》
CSCD
北大核心
2013年第4期602-606,共5页
Control Engineering of China
基金
国家自然科学基金资助项目(61104073)
关键词
预测函数
分数阶PID
PID
性能指标
predictive function
fractional-order PID
PID
performance indicators
