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This paper proposes an improved learning algorithm of analog compound orthogonal networks and a novel tracking control approach for nonholonomic mobile robots by integrating the neural network into the backstepping technique. The adaptive control is derived from continuously tuning parameters using the analog neural network in the backstepping control law. The proposed control approach for the mobile...
An adaptive controller of nonlinear PID-based analog neural networks is developed for the velocity- and orientation-tracking control of a nonholonomic mobile robot. A superb mixture of a conventional PID controller and a neural network, which has powerful capability of continuously online learning, adaptation and tackling nonlinearity, brings us the novel nonlinear PID-based analog neural network...
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