arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1306.3683math.OCcs.SYeess.SY

最优分数阶混合模糊PID控制器性能比较:用于具有死区的分数阶过程的控制

Performance Comparison of Optimal Fractional Order Hybrid Fuzzy PID Controllers for Handling Oscillatory Fractional Order Processes with Dead Time

Jadavpur University(贾达普大学);University of Southampton(南安普顿大学);Bhabha Atomic Research Centre(巴哈原子研究中心)

Saptarshi Das, Indranil Pan, Shantanu Das

AI总结:

本文研究了基于模糊逻辑的PID控制器,通过不同形式的模糊推理组合设计了分数阶混合模糊PID控制器,用于处理具有死区的分数阶过程,比较了不同控制器结构的性能。

摘要:

本文研究了基于模糊逻辑的PID控制器,考虑了通过将比例、积分和微分作用与不同形式的模糊推理相结合的几种混合控制器组合。在设计一组分解的分数阶混合模糊PID控制器时,使用了分数阶误差信号速率和分数阶控制信号积分。输入和输出缩放因子(SF)以及积分-微分算子通过实编码遗传算法(GA)进行调节,以同时考虑控制回路误差指数和控制信号,从而产生最优闭环性能。三种不同类别的分数阶振荡过程,具有不同水平的时间常数和时间延迟的相对主导性,被用来测试所提出混合分数阶模糊PID控制器的比较优势。不同FO模糊PID控制器结构的性能比较是在最优设定点跟踪、负载扰动抑制和操纵变量最小变化或较小执行器需求等方面进行的。此外,多目标非支配排序遗传算法(NSGA-II)被用来研究每个控制器结构在处理三种不同过程时设定点跟踪与控制信号、设定点跟踪与负载扰动性能之间的帕累托最优权衡。

英文摘要:

Fuzzy logic based PID controllers have been studied in this paper, considering several combinations of hybrid controllers by grouping the proportional, integral and derivative actions with fuzzy inferencing in different forms. Fractional order (FO) rate of error signal and FO integral of control signal have been used in the design of a family of decomposed hybrid FO fuzzy PID controllers. The input and output scaling factors (SF) along with the integro-differential operators are tuned with real coded genetic algorithm (GA) to produce optimum closed loop performance by simultaneous consideration of the control loop error index and the control signal. Three different classes of fractional order oscillatory processes with various levels of relative dominance between time constant and time delay have been used to test the comparative merits of the proposed family of hybrid fractional order fuzzy PID controllers. Performance comparison of the different FO fuzzy PID controller structures has been done in terms of optimal set-point tracking, load disturbance rejection and minimal variation of manipulated variable or smaller actuator requirement etc. In addition, multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used to study the Pareto optimal trade-offs between the set point tracking and control signal, and the set point tracking and load disturbance performance for each of the controller structure to handle the three different types of processes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑