Mutual Synchronization of Multiple Robot Manipulators with Unknown Dynamics
Journal of Intelligent and Robotic Systems
Cooperative tracking of multiple agents with uncertain nonlinear dynamics and fixed time delays
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
Output feedback adaptive robust NN control for a class of nonlinear discrete-time systems
ISNN'13 Proceedings of the 10th international conference on Advances in Neural Networks - Volume Part II
Information Sciences: an International Journal
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This brief studies an adaptive neural output feedback tracking control of uncertain nonlinear multi-input-multi-output (MIMO) systems in the discrete-time form. The considered MIMO systems are composed of n subsystems with the couplings of inputs and states among subsystems. In order to solve the noncausal problem and decouple the couplings, it needs to transform the systems into a predictor form. The higher order neural networks are utilized to approximate the desired controllers. By using Lyapunov analysis, it is proven that all the signals in the closed-loop system is the semi-globally uniformly ultimately bounded and the output errors converge to a compact set. In contrast to the existing results, the advantage of the scheme is that the number of the adjustable parameters is highly reduced. The effectiveness of the scheme is verified by a simulation example.