Decentralized output feedback adaptive NN tracking control of interconnected nonlinear time-delay systems with prescribed performance

This paper studies the decentralized output feedback adaptive NN tracking control problem for interconnected nonlinear time-delay systems with prescribed performance. By using the novel states transformation, the prescribed tracking performance can be guaranteed. Firstly, we design the decentralized filters independent of time delay to estimate the unmeasured state variables. By estimating the bounds of the unknown parameters instead of themselves, it can avoid the over-estimation problem. Then, by using RBF (radial basis function) neural network (NN) to approximate the unavailable time-delay functions, we construct the adaptive neural network output feedback controller with corresponding adaptive laws. It is proved that all the signals of the overall closed-loop systems are ultimately uniformly bounded. Finally, simulation examples are presented to verify the effectiveness of the theoretic results obtained.