Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Iterative Learning Control for Deterministic Systems
Iterative Learning Control for Deterministic Systems
Adaptive Filtering: Algorithms and Practical Implementation
Adaptive Filtering: Algorithms and Practical Implementation
Learning feedforward control using a Dilated B-spline network: frequency Domain Analysis and design
IEEE Transactions on Neural Networks
Feedback analysis of U-model via small gain theorem
ACMOS'08 Proceedings of the 10th WSEAS International Conference on Automatic Control, Modelling & Simulation
MIMO U-model based control: real-time tracking control and feedback analysis via small gain theorem
WSEAS Transactions on Circuits and Systems
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In this paper, a learning feedforward controller (LFFC) using the U-model is proposed for a better tracking control of multivariable nonlinear systems over a finite time interval. The multivariable system is modelled using the U-model and the LFFC is established using Newton-Raphson method. U-model significantly simplifies the online synthesis of the feedforward control law. The proposed technique is verified on 2-link robot manipulator in real-time. The performance of the proposed U-model based LFFC is compared with a number of schemes under varying load conditions.