In this article, the adaptive tracking control problem is considered for a class of uncertain nonlinear systems with input delay and saturation. To compensate for the effect of the input delay and saturation, a compensation system is designed.Radial basis function neural networks are directly utilized to approximate the unknown nonlinear functions. With the aid of the backstepping method, novel adaptive neural network tracking controllers are developed, which can guarantee all the signals in the closed-loop system are semiglobally uniformly ultimately bounded, and the system output can track the desired signal with a small tracking error. In the end, a simulation example is given to illustrate the effectiveness of the proposed methods.
K E Y W O R D Sinput delay, neural networks, nonlinear systems, saturation
INTRODUCTIONIn recent years, adaptive control problem for nonlinear systems has attracted considerable attention and remarkable developments have been obtained in nonlinear control area. Among these results, adaptive control by using backstepping technique has received much attention because of its advantages over the conventional approaches (see References 1-5 and references therein). In addition, fuzzy logic systems and neural network have also be widely used in nonlinear control area due to their ability of approximating unknown nonlinear functions. 6-10 Although fruitful results have been obtained for nonlinear systems, there are still some challenging problems waiting to be solved. It is well known that control problem of input-delayed systems is one of the fundamental problems for time-delay systems because of its practical and theoretical significance. At present, many approaches have been proposed for system with state delay (see References 9-13). However, they all ignored the input delay. Compared with state delay, control problem of input delay is more complicated and the traditional Lyapunov-Krasovskii functional based methods are not effective to deal with the input delay. Therefore, it is noteworthy for us to investigate the systems with input delays. A basic idea in dealing with input delay is the predictor feedback. 14,15 However, traditional predictor-based methods have difficulties in practical implementation because of the distributed term. Therefore, to avoid the infinite-dimensionality of feedback laws, truncated predictor feedback was studied in References 16 to 20 to ignore the distributed term.Although fruitful results have been obtained for linear input-delay systems, the adaptive control problem for uncertain nonlinear system is still a challenging problem because nonlinear systems' states are not easy to be predicted with the existence of the nonlinearity and uncertainty. Considering this factor, some other methods need to be proposed to deal with the input delay. At present, there are a few results reported on uncertain nonlinear systems with input delay. 21-34 Specifically, Int J Robust Nonlinear Control. 2020;30:2593-2610.wileyonlinelibrary.com/journal/rnc