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A Neural-Network-Based Robust Control Strategy Applying to Omnidirectional Lower Limbs Rehabilitation Robot during Centre-of-gravity Shift

机译:基于神经网络的鲁棒控制策略,其在重心换切期间应用于全向下肢康复机器人

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Motion control of mobile rehabilitation robot during centre-of-gravity shift is an intrinsic problem with mechanism. This paper deals with the tracking control of an omnidirectional lower limbs rehabilitation robot during centre-of-gravity shift. The main research contents of this paper consist of two parts: 1) The dynamic model that considered centre-of-gravity position is integrated within the control framework. 2) A robust control strategy based on neural network structure is developed and used to achieve the desired trajectories. Simulation tests are performed and demonstrate the feasibility and efficacy of the proposed method.
机译:移动康复机器人的运动控制在重心换切期间是机构的内在问题。本文涉及在重心换切期间的全向下肢康复机器人的跟踪控制。本文的主要研究内容包括两个部分:1)将重心位置的动态模型集成在控制框架内。 2)开发了一种基于神经网络结构的鲁棒控制策略,用于实现所需的轨迹。进行仿真测试并证明所提出的方法的可行性和功效。

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