摘要
针对一类具有输出响应波动大、时滞性大的问题,提出了一种基于增广非最小状态空间(NMSS)模型的预测函数控制(PFC)算法。该算法利用阶跃响应数据建立传递函数模型,将其离散化并转换为状态空间模型的形式,通过将延迟输入与误差扩展到状态变量中,得到一种增广的状态空间模型。为了增强输入控制量的规律性,提高相应的快速性和准确性,把输入表示为若干基函数线性组合,最后求出基函数系数便可求得控制信号。仿真结果表明该算法有较好的控制精度和良好的跟踪控制性能。
The predictive functional control algorithm based on extended non-minimal state space model(NMSS)is proposed to solve the problem of big fluctuation of output and large delay.A transfer function model was set up via the step-response then discretized and transformed into state space model.The extended state variables consisted of delayed input and error.To enhance the regularity,quickness and accuracy of the input control variable,the input was expressed as linear combination of some basis function.Finally the control signal can be obtained through the coefficient of basis function.The simulation results showed the proposed algorithm had good control accuracy and tracking ability.
出处
《辽宁石油化工大学学报》
CAS
2017年第1期61-64,80,共5页
Journal of Liaoning Petrochemical University
基金
国家自然科学基金项目(61673199)
辽宁省高校优秀人才支持计划项目(LJQ2015061)
关键词
非最小状态空间
预测函数控制
基函数
控制精度
跟踪控制
Non-minimal state space
Predictive functional control
Basis functional
Control accuracy
Tracking ability
