Nonlinear approximations using elliptic basis function networks
Circuits, Systems, and Signal Processing
Stochastic choice of basis functions in adaptive function approximation and the functional-link net
IEEE Transactions on Neural Networks
Adaptive stick-slip friction and backlash compensation using dynamic fuzzy logic system
Applied Soft Computing
Brief paper: Modeling and identification of systems with backlash
Automatica (Journal of IFAC)
Recursive identification algorithm for dynamic systems with output backlash and its convergence
International Journal of Applied Mathematics and Computer Science - Special Section: Robot Control Theory Cezary Zielinski
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A dynamic inversion compensation scheme is presented for backlash. The compensator uses the backstepping technique with neural networks (NN) for inverting the backlash nonlinearity in the feedforward path. Instead of a derivative, which cannot be implemented, a filtered derivative is used. Full rigorous stability proofs are given using filtered derivative. Compared with adaptive backstepping control schemes, we do not require the unknown parameters to be linear parametrizable. No regression matrices are needed. The technique provides a general procedure for using NN to determine the dynamic preinverse of an invertible dynamical system. A modified Hebbian algorithm is presented for NN tuning which yields a stable closed-loop system. Using this method yields a relatively simple adaptation structure and offers computational advantages over gradient descent based algorithms.