一类非线性时滞系统的鲁棒间接自适应控制

针对一类不确定非线性时滞系统，基于变结构控制原理，利用多层神经网络逼近的能力，提出具有投影算法的间接自适应控制方案。该方案通过监督控制器保证闭环系统所有信号有界，并引入综合误差的自适应补偿项来消除建模误差的影响。理论分析证明跟踪误差收敛到零，仿真结果表明该方法有的效性。

Robust indirect adaptive control for a class of nonlinear time-delay systems

A new indirect adaptive neural network control scheme with projection algorithm was developed for a class of uncertain nonlinear time-delay systems in this paper. The design was based on the principle of variable structure. Multi-layer Neural Networks (MNNs) were utilized to approximate for unknown plant functions. With the help of a supervisory controller, the resulted closed-loop system was globally stable in the sense that all signals involved were uniformly bounded. Furthermore, the adaptive compensation term of the optimal approximation error was introduced to minimize the effects of modeling error. By theoretical analysis, it is shown that the tracking error converges to zero. Simulation results demonstrate the effectiveness of the approach.