Journal of Liaoning Petrochemical University

Journal of Liaoning Petrochemical University ›› 2017, Vol. 37 ›› Issue (1): 61-64.DOI: 10.3969/j.issn.1672-6952.2017.01.012

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Research of Predictive Functional Control Based on Extended NMSS Model

  

  • Received:2016-09-06 Revised:2016-10-09 Published:2017-02-24 Online:2017-03-16

基于增广NMSS模型的预测函数控制研究

黄武程1,苏成利1,施惠元1,2,蔡宏斌2   

  1. 1.辽宁石油化工大学信息与控制工程学院,辽宁抚顺113001;2.西北工业大学自动化学院,陕西西安710072
  • 通讯作者: 苏成利(1977-),男,博士,教授,从事模型预测控制、工业过程的先进控制与优化等方向研究;E-mail:sclwind@ sina.com。
  • 作者简介:黄武程(1990-),男,硕士研究生,从事工业过程控制优化、模型预测控制方向研究;E-mail:m18341350279@163.com。
  • 基金资助:
    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)。

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Abstract:

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.   

Key words: Non-minimal state space, Predictive functional control, Basis functional, Control accuracy, Tracking ability

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。

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

Cite this article

HuangWucheng, SuChengli, ShiHuiyuan, CaiHongbin. Research of Predictive Functional Control Based on Extended NMSS Model[J]. Journal of Liaoning Petrochemical University, 2017, 37(1): 61-64.

黄武程, 苏成利, 施惠元, 蔡宏斌. 基于增广NMSS模型的预测函数控制研究[J]. 辽宁石油化工大学学报, 2017, 37(1): 61-64.

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