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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,速度和加速度误差的离线估计。在奇异描述符系统的频谱分析框架中解决了此问题,并引入了一类鲁棒估计。这些估计器在学习控制算法的实现中的使用已在原型操纵器上进行了测试,并报告了实验结果。结论是,只要给出用于速度和加速度的鲁棒估计器,迭代学习控制就可以在实际操纵器上成功实现。

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