| 采用神经网络和遗传算法组合的自学习模糊控制器 |
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| 引用本文： | 方建安,邵世煌.采用神经网络和遗传算法组合的自学习模糊控制器[J].东华大学学报(自然科学版),1995(2). |
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| 作者姓名： | 方建安 邵世煌 |
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| 作者单位： | 中国纺织大学自动化与电子信息工程系
(方建安)，中国纺织大学自动化与电子信息工程系(邵世煌) |
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| 摘 要： | 本文提出一种新型的、采用神经网络和遗传算法组合自学习构造模糊控制器的方法。该方法将神经网络的实时增强学习能力融合于遗传算法的全局搜索中,提高了系统的收敛速度、实时学习能力和控制性能,而不需要提供系统动力学知识和先验控制经验。作者以倒立摆系统和家用空调器作为控制对象,通过仿真计算检验了该方法的有效性。
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| 关 键 词： | 神经网络 模糊逻辑 自组织控制 遗传算法 组合 |
SELF-LEARNING FUZZY CONTROLLERS BASED ON NEURAL NETWORK WITH GENETIC ALGORITHM |
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| Fang Jianan,Shao Shihuang.SELF-LEARNING FUZZY CONTROLLERS BASED ON NEURAL NETWORK WITH GENETIC ALGORITHM[J].Journal of Donghua University,1995(2). |
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| Authors: | Fang Jianan Shao Shihuang |
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| Institution: | Department of Automation and Electrical Information Engineering |
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| Abstract: | This paper suggests a new method for self-earning fuzzy controllers based on neural network with genetic algorithm. In the proposed method, the real-time reinforcement learning ability of neural networks is improved by using genetic algorithm for globally searching a set of optimal fuzzy control rules,which enhance the convergence rate, real-ime learning ability and control performance of the system without further knowledge of the system dynamics and prior control experience. Simulation results using inverted pendulum and household air-conditioner as objects of control indicate the effectiviness of the authors proposed method. |
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| Keywords: | neural networks fuzzy logic self-organizing control genetic algorithm integrating |
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