Control of nonholonomic wheeled mobile robots by state feedback linearization
International Journal of Robotics Research
Tracking control of mobile robots: a case study in backstepping
Automatica (Journal of IFAC)
An orthogonal neural network for function approximation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Control of a nonholonomic mobile robot using neural networks
IEEE Transactions on Neural Networks
Adaptive backstepping sliding mode control for nonlinear systems with neural networks
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Tracking control of a nonholonomic mobile robot using compound cosine function neural networks
Intelligent Service Robotics
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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 robot has the properties to quickly drive the position error to zero and to indicate better smooth movement in the tracking control process. These features are due to continuous online learning and adaptive capability of analog neural networks. Simulation results demonstrate that the proposed control approach is effective and has better control performance.