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Real-time application of a constrained predictive controller based on dynamic neural networks with feedback linearization

机译:基于动态神经网络的受限预测控制器的实时应用反馈线性化

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This paper describes an experimental application of constrained predictive control and feed-back linearisation based on dynamic neural networks. It also verifies experimentally a method for handling input constraints, which are transformed by the feedback linearisation mappings. A performance comparison with a PID controller is also provided. The experimental system consists of a laboratory based single link manipulator arm, which is controlled in real time using MATLAB/SIMULINK together with data acquisition equipment.
机译:本文介绍了基于动态神经网络的受约束预测控制和反馈线性的实验应用。它还验证了一种用于处理输入约束的方法,该方法由反馈线性映射转换。还提供了与PID控制器的性能比较。实验系统包括基于实验室的单链路机械手臂,其实时使用MATLAB / Simulink与数据采集设备一起控制。

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