In this article, a novel neural network (NN) optimal control approach using adaptive critic designs is developed for nonlinear discrete‐time (DT) systems with time delays. First, to eliminate the delay term of control input, a time‐delay matrix function is developed by designing a M network. Furthermore, the cost function is approximated by the critic NN, and the control signal can be obtained directly by using the information of critic NN according to the equilibrium condition. In addition, to shorten the learning time and reduce the computational burden in the control process, a novel control strategy with less adjustable parameters for the time‐delay DT nonlinear systems is proposed in this article, in which the norm of the weight estimations of critic NN is updated to generate a novel long‐term performance function. The proposed control algorithm using adaptive critic designs has the advantage of reducing adaptive learning parameters and lessening calculative burden. The Lyapunov stability analysis shows that the time‐delay DT controlled systems can be uniformly ultimately bounded stable. Finally, three simulations are presented to demonstrate the control performance of the developed method.

中文翻译：

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非线性时滞系统的新型神经网络离散时间最优控制设计

在本文中，针对具有时间延迟的非线性离散时间（DT）系统，开发了一种采用自适应批评家设计的新型神经网络（NN）最优控制方法。首先，为了消除控制输入的延迟项，通过设计一个M来开发一个时延矩阵函数网络。此外，通过评论者NN来近似成本函数，并且可以根据平衡条件通过使用评论者NN的信息直接获得控制信号。另外，为了缩短学习时间并减少控制过程中的计算负担，本文提出了一种时滞DT非线性系统参数较少可调整的新型控制策略，该方法以评论者的权重估计为准。 NN被更新以生成新颖的长期性能函数。所提出的使用自适应批评者设计的控制算法具有减少自适应学习参数和减轻计算负担的优点。Lyapunov稳定性分析表明，时延DT控制的系统可以最终统一稳定。最后，