系统仿真学报 ›› 2015, Vol. 27 ›› Issue (11): 2778-2783.

• 信息、控制、决策与仿真 • 上一篇    下一篇

一类基于预测的自适应PID控制器

刘艳君, 毛亚文   

  1. 江南大学教育部轻工过程先进控制重点实验室,无锡 214122
  • 收稿日期:2014-09-25 修回日期:2014-11-12 出版日期:2015-11-08 发布日期:2020-08-05
  • 作者简介:刘艳君(1983-),女,江苏靖江,博士,讲师,研究方向为系统辨识理论与方法,自适应控制等;毛亚文(1991-),女,江苏海安,硕士生,研究方向为系统辨识理论与方法。
  • 基金资助:
    国家自然科学基金(61304138, 61473136); 江苏省自然科学基金(BK20130163)

A Class of Prediction Based Adaptive PID Controller

Liu Yanjun, Mao Yawen   

  1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China
  • Received:2014-09-25 Revised:2014-11-12 Online:2015-11-08 Published:2020-08-05

摘要: PID (proportional integral derivative)控制器广泛应用于各种工业过程,但实际被控对象的机理、复杂程度和环境条件各不相同,常规整定方法很难维持满意的效果。为了增强控制系统的鲁棒性和稳定性,先进的PID控制算法得到了广泛的关注。针对常见的带积分受控自回归滑动平均(CARIMA)模型提出了一类基于预测的自适应控制算法,使得PID参数能够随着对象模型参数的变化而变化,实现在线整定。该递推算法是通过在给定时域内极小化性能指标函数而得到的,其中性能指标函数考虑了某一给定范围内给定输入和预测输出的二次偏差以及控制量,在线辨识阶段则采用递推最小二乘算法。仿真结果证实该方法有很好的自适应力和鲁棒性。

关键词: PID控制器, CARIMA模型, 预测, 在线辨识, 自适应力

Abstract: The PID controller has been widely used in various industrial processes. However, for real practical control plants, their mechanisms, structures and operation conditions are different, and conventional tuning methods cannot always work in a desirable state. In order to improve the robustness and the stability of the control systems, advanced PID control algorithms have been attracted much attention. A prediction based adaptive control algorithm is proposed for CARIMA models, where the PID parameters can be tuned adaptively according to the parameters of the control plant. The key is minimizing a performance index which considers the quadratic predicted output, over the set point, as well as the control efforts, over a time horizon. For the online identification step, the recursive extended least squares estimation technique is implemented. The adaptability and the robustness of the proposed algorithm are validated by simulation results.

Key words: PID controller, CARIMA models, prediction, on-line identification, adaptability

中图分类号: