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Fuzzy Neural Network Controller Based on Hybrid GA-BP Algorithm

机译:基于混合GA-BP算法的模糊神经网络控制器

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This paper presents a hybrid GA-BP algorithm for fuzzy neural network controller (FNNC). BP algorithm is a method to monitor learning, easily realized and with good local searching ability. But it depends too much on the the initial states of the network. Genetic algorithm is a random search algorithm which has strong global searching ability. The hybrid GA-BP algorithm ensure the global convergence of learning by genetic algorithm, overcomes the BP algorithm's dependency on the initial states on the one hand. On the other hand, combined with the BP algorithm overcome the simple genetic algorithm's randomness, improve the searching efficiency. The simulations on the inverted pendulum problem show good performance and robustness of the proposed fuzzy neural network controller based on hybrid GA-BP algorithm.
机译:本文介绍了一种用于模糊神经网络控制器(FNNC)的混合GA-BP算法。 BP算法是一种监控学习,容易实现和具有良好本地搜索能力的方法。但它在网络的初始状态上取决于太多。遗传算法是一种随机搜索算法,具有强大的全局搜索能力。 Hybrid GA-BP算法确保通过遗传算法进行全局学习融合,克服了一方面对初始状态的依赖性。另一方面,结合BP算法克服了简单的遗传算法的随机性,提高了搜索效率。倒立摆的仿真显示了基于混合GA-BP算法的提出模糊神经网络控制器的良好性能和鲁棒性。

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