基于模糊控制器的直流电动机模型参考线性自适应控制

A. Suresh kumar, M. Subba Rao, Y. Babu
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引用次数: 19

摘要

本文研究了传统的模型参考自适应控制(MRAC),用模糊线性自适应模型参考自适应控制方案代替PI控制等传统控制技术。模型参考自适应控制(Model Reference Adaptive Control, MRAC)速度控制系统在较宽的速度需求范围内,特别是低速时,不能获得一致的满意性能,并且没有明确的规则指导设计者选择自适应增益。模糊逻辑模型参考自适应控制无论输入量大小如何都能保持满意的响应。与传统的MRAC相比,它提高了直流驱动器的性能。由此得到的驱动系统的性能,正在形成一套具有模型参考模糊自适应控制的试验条件。结合参考模型,对负载扰动下的驱动性能进行了测试。本文还比较了模型参考模糊自适应方案与传统MRAC方案的性能。本工作采用MATLAB-SIMULINK进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model reference linear adaptive control of DC motor using fuzzy controller
This paper deals with the conventional model reference adaptive control (MRAC) and replaces conventional control technique such as PI control with model reference adaptive control scheme with fuzzy linear adaptation. The Model Reference Adaptive Control (MRAC) speed control systems do not achieve consistent satisfactory performance over wide range of speed demand, especially at low speed and there is no defined rule to guide designers to choose the adaptation gains. The fuzzy logic model reference adaptive control maintains satisfactory response irrespective of the magnitude of the inputs. It enhances the performance of the DC drive compared to conventional MRAC. The performance of the drive system, thus obtained, is forming a set of test conditions with model reference fuzzy adaptive control. The performance of the drive is tested for load disturbances along with reference model. This work also compares the performance of Model Reference Fuzzy Adaptive scheme over conventional MRAC. This work is carried out by using MATLAB-SIMULINK.
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