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首页> 外文期刊>Zeitschrift fur Angewandte Mathematik und Mechanik >Reduction of the on-line measurement and control expenses by adaptive stochastic path planning
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Reduction of the on-line measurement and control expenses by adaptive stochastic path planning

机译:通过自适应随机路径规划减少在线测量和控制费用

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摘要

In the optimal control of dynamic systems, e.g., in the control of industrial or service robots, the standard procedure is to determine first off-line an optimal open loop control, and correct then the inevitable deviation of the trajectory or performance of the system from the prescribed values by on-line measurement and control actions which may be very expensive. By adaptive stochastic path planning and control (ASPPC), i.e. by incorporating the available a priori and statistical information on the unknown model parameters of the dynamic system and its working environment into the off-line caned on-line control process by means of stochastic optimization methods, the deviation between the actual and prescribed trajectory can be reduced to a large extent. [References: 3]
机译:在动态系统的最佳控制中,例如在工业或服务机器人的控制中,标准程序是首先离线确定最佳开环控制,然后纠正系统的轨迹或性能不可避免的偏离。通过在线测量和控制操作可能会花费非常昂贵的规定值。通过自适应随机路径规划和控制(ASPPC),即通过随机优化将动态系统及其工作环境的未知模型参数的可用先验和统计信息合并到离线罐装在线控制过程中方法中,实际轨迹和规定轨迹之间的偏差可以大大减小。 [参考:3]

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