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T-S fuzzy neural network control for autonomous underwater vehicles
Author(s): 
Pages: 99-104
Year: Issue:  7
Journal: Electric Machines and Control

Abstract: 针对水下机器人模糊神经网络控制器运算量大和对强外界扰动的鲁棒性差及存在滞后性的问题,提出基于混合学习算法的水下机器人T-S型模糊神经网络控制方法.采用免疫遗传算法离线优化和神经网络自学习在线调整隶属函数的参数,从而减少神经网络的运算量,增强水下机器人对环境变化的反应能力.采用T-S模型,由后件网络动态调整模糊规则,提高控制系统的适应性.通过某微小型水下机器人的仿真和外场实验验证方法的可行性和优越性...
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