Robot Dynamics and Control
Nonlinear and Adaptive Control Design
Nonlinear and Adaptive Control Design
Automatica (Journal of IFAC)
Robust backstepping control of nonlinear systems using neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Brief Adaptive control for output feedback nonlinear systems in the presence of modeling errors
Automatica (Journal of IFAC)
Adaptive neural control of uncertain MIMO nonlinear systems
IEEE Transactions on Neural Networks
Robust and adaptive backstepping control for nonlinear systems using RBF neural networks
IEEE Transactions on Neural Networks
Automatica (Journal of IFAC)
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This works presents a neural-adaptive control strategy for trajectory tracking for a two-link flexible joint robot, with experimental results. The method of backstepping with tuning functions (using analytic differentiation) guides the design, rather than using neural approximation of derivatives. Traditional tuning function design results in a weight update dominated by the last error in the backstepping design, not the output error. The novel method in this paper weights the errors in the tuning function so that the output error becomes significant in training. An additional modification ensures robustness to approximation errors. Experimental results show the improved performance compared to both derivative-estimation and normal tuning function methods.