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Hybrid Model Predictive Control for Stabilization of Wheeled Mobile Robots Subject to Wheel Slippage

机译:用于稳定轮式移动机器人的混合模型预测控制,挡轮滑动

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This paper studies the problem of stabilizing wheeled mobile robots (WMRs) subject to wheel slippage to a predefined set. When slippage of the wheels can occur, WMRs can be modeled as hybrid systems. Model predictive control for such systems typically results in numerical methods of combinatorial complexity. We show that recently developed embedding techniques can be used to formulate numerical algorithms for the hybrid model predictive control (MPC) problem that have the same complexity as the MPC for smooth systems. We also discuss in detail the numerical techniques that lead to efficient and robust MPC algorithms. Examples are given to illustrate the effectiveness of the approach.
机译:本文研究了将轮式移动机器人(WMRS)稳定到预定义集的轮滑移动机器人(WMRS)的问题。当发生车轮的滑动时,WMR可以被建模为混合系统。用于这种系统的模型预测控制通常导致组合复杂性的数值方法。我们表明,最近开发的嵌入技术可用于制定用于混合模型预测控制(MPC)问题的数值算法,其具有与平滑系统相同的复杂性。我们还详细讨论了导致高效且强大的MPC算法的数值技术。给出了实施例来说明该方法的有效性。

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