一类不确定非线性系统的直接自适应神经网络控制

Direct Adaptive Neural Network Control for a Class of Uncertain Nonlinear Systems

本文针对一类不确定非线性系统,提出一种新颖的系统化设计策略。该设计策略能够去除控制增益为未知非线性函数的控制输入项,并由此带来如下优点:不仅能够避免控制奇异问题,还能够简化控制系统设计。此外,该设计策略能够在宽松条件下导出简单的控制结构,便于工程实现并且能够运用到更一般的系统当中。

In this paper, a novel systematic design procedure is presented for a class of uncertain nonlinear systems. Such design procedure can remove the control input terms which contain the unknown nonlinearities as the control coefficients, and provide the following advantages. It not only avoids a possible singularity problem completely, but also simplifies the control design process. Moreover, the proposed design procedure can provide simple control structure under the relaxed conditions, which is easy to implement and can be applied to a wider class of systems.