Journal
IEEE ACCESS
Volume 6, Issue -, Pages 70035-70044Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2878772
Keywords
Adaptive control; fractional order; neural networks (NNs); input saturation; nonlinear system
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Funding
- Shandong Scientific Research Projects of Colleges and Universities [J18KA062]
- Foundation of State Key Laboratory of Automotive Simulation and Control [20171105]
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In this paper, an adaptive neural network (NN) backstepping control method is designed for a class of uncertain fractional order nonlinear systems with external disturbance and input saturation, in which the fractional Lyapunov stability theory is used to construct the controller. The complicated unknown fractional order nonlinear function is approximated by a radial basis function (RBF) NN in each step, and the virtual control law and parameters update law are presented based on the backstepping algorithm procedures. At the final step, an adaptive RBF NN controller is constructed, in which no knowledge of system uncertainty and the upper bound of the disturbance is required. Then, a theorem is presented to address that the asymptotical convergence of the tracking error can be guaranteed. The effectiveness of the proposed scheme is illustrated by two simulation examples.
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