Li Han-Xiong, Zhang Lei, Cai Kai-Yuan, Chen Guanrong
Department of MEEM, City University of Hong Kong, China.
IEEE Trans Syst Man Cybern B Cybern. 2005 Dec;35(6):1283-94. doi: 10.1109/tsmcb.2005.851538.
Many fuzzy control schemes used in industrial practice today are based on some simplified fuzzy reasoning methods, which are simple but at the expense of losing robustness, missing fuzzy characteristics, and having inconsistent inference. The concept of optimal fuzzy reasoning is introduced in this paper to overcome these shortcomings. The main advantage is that an integration of the optimal fuzzy reasoning with a PID control structure will generate a new type of fuzzy-PID control schemes with inherent optimal-tuning features for both local optimal performance and global tracking robustness. This new fuzzy-PID controller is then analyzed quantitatively and compared with other existing fuzzy-PID control methods. Both analytical and numerical studies clearly show the improved robustness of the new fuzzy-PID controller.
当今工业实践中使用的许多模糊控制方案都基于一些简化的模糊推理方法，这些方法虽然简单，但却以牺牲鲁棒性、模糊特性缺失和推理不一致为代价。本文引入最优模糊推理的概念以克服这些缺点。主要优点在于，将最优模糊推理与PID控制结构相结合，将产生一种新型的模糊PID控制方案，该方案具有局部最优性能和全局跟踪鲁棒性的固有最优调整特性。然后对这种新型模糊PID控制器进行了定量分析，并与其他现有的模糊PID控制方法进行了比较。分析和数值研究均清楚地表明了新型模糊PID控制器的鲁棒性得到了提高。
