New methodology for analytical and optimal design of fuzzy PID controllers
New methodology for analytical and optimal design of fuzzy PID controllers
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DOI：
10.1109/91.797977
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发表时间：
1999-10-01
影响因子：
11.9
通讯作者：
Gosine, RG
中科院分区：
文献类型：
--
作者：
Hu, B;Mann, GKI;Gosine, RG
本文介绍了一种新的方法，系统设计的模糊PID控制器的理论模糊分析和遗传优化的基础上。所提出的控制器的一个重要特点是其简单的结构。它使用了一个单输入模糊推理与三个规则和最多六个调整参数。一个封闭形式的解决方案的控制行动的非线性调谐参数的定义。在误差域中显式推导了非线性比例增益，提出了一种保守的设计策略，实现了一种性能可调的PID模糊控制器。这种策略表明，模糊PID控制器应该能够产生一个线性函数，从它的非线性调整的系统，建议的PID系统是能够产生一个密切的近似的线性函数近似的GPP系统。该GPP系统结合了用于优化的遗传求解器，将提供相对于特定性能标准（即，响应误差、稳定性或鲁棒性）。提出了评价模糊控制器非线性设计的两个指标：线性逼近指数（LAT）和非线性变化指数（NVI）。所提出的控制系统已被应用到几个一阶，二阶和五阶过程。仿真结果表明，所提出的模糊PID控制器产生上级控制性能比传统的PID控制器，特别是在处理由于时间延迟和饱和的非线性。
This paper describes a new methodology for the systematic design of fuzzy PID controllers based on theoretical fuzzy analysis and genetic-based optimization. An important feature of the proposed controller is its simple structure. It uses a one-input fuzzy inference with three rules and at most six tuning parameters. A closed-form solution for the control action is defined in terms of the nonlinear tuning parameters. The nonlinear proportional gain is explicitly derived in the error domain, A conservative design strategy is proposed for realizing a guaranteed-PID-performance (GPP) fuzzy controller. This strategy suggests that a fuzzy PID controller should be able to produce a linear function from its nonlinearity tuning of the system, The proposed PID system is able to produce a close approximation of a linear function for approximating the GPP system. This GPP system, incorporating with a genetic solver for the optimization, will provide the performance no worse than the corresponding linear controller with respect to the specific performance criteria (i.e., response error, stability, or robustness). Two indexes, linearity approximation index (LAT) and nonlinearity variation index (NVI), are suggested for evaluating the nonlinear design of fuzzy controllers. The proposed control system has been applied to several first-order, second-order, and fifth-order processes. Simulation results show that the proposed fuzzy PID controller produces superior control performance than the conventional PID controllers, particularly in handling nonlinearities due to time delay and saturation.