直流电机模糊PID控制

2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG) Pub Date : 2020-07-01 DOI:10.1109/CPE-POWERENG48600.2020.9161668

L. Palma, R. Antunes, P. Gil, Vasco Brito

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引用次数: 3

摘要

本文研究了非线性动态系统中的TSK型模糊PID控制器。基于粒子群优化(PSO)的控制器增益整定设计框架，假设非线性系统由人工神经网络逼近，从而得到基于TSK模糊PID控制的整体鲁棒控制方法。通过对包括直流电机在内的非线性动态过程的仿真和实验验证了该控制策略的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Takagi-Sugeno-Kang fuzzy PID control for DC electrical machines

This paper deals with Takagi-Sugeno-Kang (TSK) type fuzzy PID controllers in the context of nonlinear dynamic systems. The design framework for tuning the controller gains depends on particle swarm optimization (PSO), assuming the nonlinear system approximated by an artificial neural network, leading to an overall robust control methodology based on TSK fuzzy PID control. Obtained data and information from simulations and experimental tests considering a nonlinear dynamic process including a DC electrical machine confirm the effectiveness of the control strategy.

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来源期刊

2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)

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