Abstract
This paper develops an adaptive neural control scheme for chaotic permanent magnet synchronous motor with asymmetric input saturation and full-state constraints. To solve the state constrain problem, a barrier Lyapunov function is introduced. Then, a sliding-mode differentiator is designed to avoid the “explosion of complexity” issue. A simulation example is given to verify the validity of the proposed scheme.
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