基于案例推理的PID控制器参数认知整定方法

Cognitive Tuning Method Based on Case-Based Reasoning for PID Controller's Parameters

  • 摘要: 针对PID(proportional-integral-derivative)整定方法存在模型辨识困难、调节时间长、临界稳定点难以确定等问题,提出一种基于案例推理(case-based reasoning,CBR)的PID控制器参数认知整定方法(cognitive tuning based on case-based reasoning,CTCBR).设计具有动态学习功能的案例推理模型新结构,借鉴多属性决策思想改进案例检索策略,并运用多目标评价准则对参数整定后的预期效果进行评价,从而得到一种具有自学习能力的PID参数认知整定方法.与典型方法对比,该方法能够获得更好的控制性能,同时也能提高PID控制器系统的适应性和整定成功率.

     

    Abstract: The proportional-integral-derivative (PID) tuning process has inherent problems, such as difficulty in identifying the model, a long adjustment time, and difficulty in determining the critical stable point. In this study, a cognitive tuning method is proposed based on case-based reasoning (CTCBR) for the parameters of the PID controller. Firstly, a new case-based reasoning (CBR) model with dynamic learning functions is designed, which adopts multiple attributes decision-making to improve the case retrieval strategy. Multiobjective evaluation criteria are then used to evaluate the expected effect after parameter tuning. Finally, a cognitive tuning method for PID parameters with a self-learning ability is obtained. Compared to other typical methods, an improved performance control is achieved, which improves the adaptability and tuning success rate of a PID controller system.

     

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