Adaptive control of flexible joint manipulators
Systems & Control Letters
Automatica (Journal of IFAC)
Robot Dynamics and Control
Neural Network Control of Robot Manipulators and Nonlinear Systems
Neural Network Control of Robot Manipulators and Nonlinear Systems
Iterative Learning Control: Brief Survey and Categorization
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Constrained motion control of flexible robot manipulators based on recurrent neural networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Multilayer neural-net robot controller with guaranteed tracking performance
IEEE Transactions on Neural Networks
Neural-network control of mobile manipulators
IEEE Transactions on Neural Networks
Neural-network predictive control for nonlinear dynamic systems with time-delay
IEEE Transactions on Neural Networks
Self-Organizing Adaptive Fuzzy Neural Control for a Class of Nonlinear Systems
IEEE Transactions on Neural Networks
Adaptive Fuzzy-Neural-Network Control for Maglev Transportation System
IEEE Transactions on Neural Networks
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This paper considers an output feedback learning control for a class of uncertain nonlinear systems with flexible components. The distinct time delay caused by system flexibility leads to the phase lag phenomenon and low system bandwidth. Therefore, the tracking problem of such systems is very difficult and challenging. To improve the tracking performance of such systems, an iterative learning control scheme using the Fourier neural network (FNN) is presented in this paper. This scheme uses only local output information for feedback. FNN employs orthogonal complex Fourier exponentials as its activation functions and the physical meaning of its hidden-layer neurons is clear. The FNN-based learning controller introduced here relies on the frequency-domain method, which converts the tracking problem in the time domain into a number of regulation problems in the frequency domain. A novel phase compensation method is introduced to deal with the phase lag phenomenon, so that the bandwidth of the closed-loop system is increased. Experiments on a belt-driven positioning table are conducted to show the effectiveness of the proposed controller.