Multilayer feedforward networks are universal approximators
Neural Networks
Mathematical models for hysteresis
SIAM Review
Locally Convergent Nonlinear Observers
SIAM Journal on Control and Optimization
State-space analysis and identification for a class of hysteretic systems
Automatica (Journal of IFAC)
Modeling and control of hysteresis in magnetostrictive actuators
Automatica (Journal of IFAC)
Direct adaptive NN control of a class of nonlinear systems
IEEE Transactions on Neural Networks
Adaptive wavelet neural network control with hysteresis estimation for piezo-positioning mechanism
IEEE Transactions on Neural Networks
Rate-dependent hysteresis modeling and compensation using least squares support vector machines
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part II
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part II
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An observer-based adaptive control scheme for piezoelectric actuators is proposed. In the developed method the classical Duhem model is adopted to describe the hysteresis exhibited in the piezoelectric actuators. Due to the unavailability of the hysteresis output, an observer-based adaptive controller, with incorporation of a pre-inversion neural network compensator for the purpose of mitigating the hysteretic effects, is designed to guarantee the stability of the adaptive system and tracking error between the position of the piezoelectric actuator and the desired trajectory to a desired precision. Simulation studies illustrate the effectiveness of the proposed method.