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arXiv 1202.5683eess.SYcs.NEcs.SY
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改进的模型降阶与分数阶PIλDμ控制器调谐,用于基于遗传编程的解析规则提取

Improved Model Reduction and Tuning of Fractional Order PIλDμ Controllers for Analytical Rule Extraction with Genetic Programming

Jadavpur University(贾达普大学);Bhabha Atomic Research Centre(巴哈原子研究中心)

Saptarshi Das, Indranil Pan, Shantanu Das, Amitava Gupta

AI总结:

本文提出一种基于遗传算法在奈奎斯特平面上的次优模型降阶新方法,并结合时域最优调谐,通过遗传编程从高阶过程数据中提取PID和分数阶PIλDμ控制器的解析调谐规则,实现了性能与复杂度的权衡。

摘要:

本文采用遗传算法(GA)进行奈奎斯特平面上的次优模型降阶新方法以及PID和分数阶(FO)PIλDμ控制器的时域最优调谐。仿真研究表明,基于奈奎斯特的新模型降阶技术优于传统的基于H2范数的降阶参数建模技术。利用调谐后的控制器参数和降阶模型参数数据集,通过遗传编程(GP)针对高阶过程测试平台开发了最优调谐规则。GP对降阶过程参数进行符号回归,演化出能最佳映射数据的调谐规则。这些调谐规则针对由误差指标和控制器努力加权和描述的最小时间域积分性能指标而开发。从报告的基于GP的最优规则提取技术的帕累托最优前沿,可以在调谐公式的复杂性和控制性能之间进行权衡。对于PID和PIλDμ控制器,将单基因和多基因GP调谐规则的有效性与原始GA控制性能进行了比较,处理了四类不同的代表性高阶过程。这些规则对过程控制工程师非常有用,因为它们继承了基于GA的调谐方法的强大功能,但无需每次运行计算密集的GA即可轻松计算。展示了PID/FOPID控制器参数随降阶过程参数变化的三维图作为操作指南。通过可信的仿真示例,还展示了所报告的GP调谐规则的参数鲁棒性。

英文摘要:

Genetic Algorithm (GA) has been used in this paper for a new approach of sub-optimal model reduction in the Nyquist plane and optimal time domain tuning of PID and fractional order (FO) PIλDμ controllers. Simulation studies show that the Nyquist based new model reduction technique outperforms the conventional H2 norm based reduced parameter modeling technique. With the tuned controller parameters and reduced order model parameter data-set, optimum tuning rules have been developed with a test-bench of higher order processes via Genetic Programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by weighted sum of error index and controller effort. From the reported Pareto optimal front of GP based optimal rule extraction technique a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP based tuning rules has been compared with original GA based control performance for the PID and PIλDμ controllers, handling four different class of representative higher order processes. These rules are very useful for process control engineers as they inherit the power of the GA based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three dimensional plots of the required variation in PID/FOPID controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP based tuning rules has also been shown with credible simulation examples.

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。

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