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Implementation of learning control techniques using descriptor systems methods

机译:使用描述符系统方法实现学习控制技术

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Learning control algorithms rely on offline estimates of generalized position, velocity, and acceleration errors. This problem is addressed in the framework of the spectral analysis of singular descriptor systems, and a class of robust estimates is introduced. The use of these estimators in the implementation of learning control algorithms has been tested on a prototype manipulator, and experimental results are reported. It is concluded that iterative learning control can be successfully implemented on real manipulators provided that robust estimators for velocity and acceleration are given.
机译:学习控制算法依赖于广义位置,速度和加速误差的离线估计。 在奇异描述符系统的频谱分析的框架内解决了该问题,并引入了一类稳定的估计。 在原型机械手上测试了在学习控制算法的实施中使用这些估算器,并报告了实验结果。 得出结论,可以在实际操纵器上成功实现迭代学习控制,条件是给出了用于速度和加速度的稳健估计。

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