A deadbeat trajectory controller for nonlinear systems via neural network: a robot case study

M. Guzelkaya, S. Kurtulan, L. Goren
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Abstract

A method for trajectory control of nonlinear systems is presented. Nonlinear feedback is used in order to obtain a linear model, and the nonlinearities and uncertainties remain are modelled by a multilayer neural network. The tracking error between the nonlinear system output and a desired trajectory is attempted to be removed by a deadbeat controller. The algorithm is applied to the trajectory control of a robot arm.<>
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基于神经网络的非线性系统无差拍轨迹控制器:以机器人为例
提出了一种非线性系统的轨迹控制方法。利用非线性反馈得到线性模型,剩余的非线性和不确定性由多层神经网络建模。非线性系统输出与期望轨迹之间的跟踪误差试图通过无差拍控制器消除。将该算法应用于机械臂的轨迹控制。
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