直流伺服电机速度控制的神经模糊控制器设计

Young-Ho Kang, Lark-Kyo Kim
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引用次数: 9

摘要

作者设计了一种神经模糊控制器,以改善用模糊控制器控制非线性系统时出现的一些问题。该模型具有快速响应、最大学习效果和缩短学习时间的特点。为了验证本文所设计的神经模糊控制器的性能,将该神经模糊模型应用于直流伺服电机。因此,该控制器不会产生PID控制器中的超调,也不会产生FLC的稳态误差。此外,它缩短了约10%的沉淀时间。此外,作者意识到他们的模型只有PID控制器当前峰值值的60%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of neuro-fuzzy controller for the speed control of a DC servo motor
The authors have designed a neuro-fuzzy controller to improve some problems that occur when the nonlinear system is controlled by a fuzzy logic controller. Their model obtains fast-time response, maximized learning effect and shortened settling time. To prove the capability of the neuro-fuzzy controller designed in this paper, this neuro-fuzzy model is applied to a DC servomotor. As a result, this controller does not produce overshoot, which occurs in the PID controller, and also does not produce the steady state error of FLC. Also, it shortens the settling time by about 10%. In addition, the authors are aware that their model has only about 60% of the value of current peak of the PID controller.
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