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Fast nonlinear model predictive control for teleoperation systems using computationally efficient optimization techniques

机译:使用高效计算优化技术的远程操作系统快速非线性模型预测控制

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The online computational load associated with Nonlinear Model Predictive Control (NMPC) is a serious barrier for its application to systems with fast dynamics. This paper addresses numerical approaches for fast and real-time feasible NMPC. The applicability of these methods to fast systems with sampling times in order of milliseconds is investigated through a nonlinear teleoperation system. The main ideas of the “real-time iteration” (RTI) approach for real-time optimization are addressed. Condensing approach to efficient structure exploitation of the described RTI scheme is then presented. The described method ensures a considerable reduction of the computational effort as required in real-time implementations. The NMPC algorithms based on these methods can therefore be carried out at higher sampling rates. The results show promising performance of the nonlinear teleoperation system using fast NMPC controller.
机译:与非线性模型预测控制(NMPC)相关联的在线计算负荷是将其应用于具有快速动态性的系统的严重障碍。本文介绍了用于快速和实时可行的NMPC的数值方法。通过非线性遥操作系统,研究了这些方法在采样时间为毫秒量级的快速系统中的适用性。提出了用于实时优化的“实时迭代”(RTI)方法的主要思想。然后介绍了对所描述的RTI方案进行有效结构开发的压缩方法。所描述的方法确保了实时实现中所需的计算量的显着减少。因此,可以以更高的采样率执行基于这些方法的NMPC算法。结果表明,使用快速NMPC控制器的非线性遥操作系统的性能令人鼓舞。

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