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针对深海采矿机器人模型和外界环境不确定性而导致其控制问题异常复杂这一难题,首先用RBF神经网络逼近系统不确定性的上界,在状态反馈的基础上,构造了基于虚拟输入的航向控制鲁棒自适应律;然后给出了左右履带速度输入与虚拟输入之间的模糊控制推理规则,提出了采矿机器人的行走控制方法.仿真结果验证了所提出方法的可行性.
In order to solve the difficult problem of complicated control problem caused by the deep sea mining robot model and the uncertainty of the external environment, RBF neural network is used to approximate the upper bound of system uncertainty. Based on the state feedback, Then the robust adaptive law is controlled. Then the inference rule of fuzzy control between left and right track speed input and virtual input is given, and the walking robot control method is proposed. The simulation results verify the feasibility of the proposed method.