IEEE Trans Neural Netw Learn Syst. 2018 Apr;29(4):993-1005. doi: 10.1109/TNNLS.2016.2642128. Epub 2017 Feb 1.
In this paper, based on the adaptive critic learning technique, the control for a class of unknown nonlinear dynamic systems is investigated by adopting a mixed data and event driven design approach. The nonlinear control problem is formulated as a two-player zero-sum differential game and the adaptive critic method is employed to cope with the data-based optimization. The novelty lies in that the data driven learning identifier is combined with the event driven design formulation, in order to develop the adaptive critic controller, thereby accomplishing the nonlinear control. The event driven optimal control law and the time driven worst case disturbance law are approximated by constructing and tuning a critic neural network. Applying the event driven feedback control, the closed-loop system is built with stability analysis. Simulation studies are conducted to verify the theoretical results and illustrate the control performance. It is significant to observe that the present research provides a new avenue of integrating data-based control and event-triggering mechanism into establishing advanced adaptive critic systems.
本文基于自适应评论家学习技术，采用混合数据和事件驱动设计方法，研究了一类未知非线性动态系统的控制问题。将非线性控制问题表述为一个二人零和微分博弈，并采用自适应评论家方法处理基于数据的优化。新颖之处在于将基于数据的学习识别器与事件驱动设计公式相结合，以开发自适应评论家控制器，从而实现非线性控制。通过构建和调整一个评论家神经网络，对事件驱动最优控制律和时间驱动最坏情况干扰律进行逼近。应用事件驱动反馈控制，构建闭环系统并进行稳定性分析。通过仿真研究验证了理论结果并展示了控制性能。值得注意的是，本研究为将基于数据的控制和事件触发机制集成到先进的自适应评论家系统的建立中提供了新的途径。
