Vega Carlos J, Suarez Oscar J, Sanchez Edgar N, Chen Guanrong, Elvira-Ceja Santiago, Rodriguez David I
IEEE Trans Neural Netw Learn Syst. 2020 Mar;31(3):854-864. doi: 10.1109/TNNLS.2019.2910504. Epub 2019 Apr 30.
A new approach for trajectory tracking on uncertain complex networks is proposed. To achieve this goal, a neural controller is applied to a small fraction of nodes (pinned ones). Such controller is composed of an on-line identifier based on a recurrent high-order neural network, and an inverse optimal controller to track the desired trajectory; a complete stability analysis is also included. In order to verify the applicability and good performance of the proposed control scheme, a representative example is simulated, which consists of a complex network with each node described by a chaotic Lorenz oscillator.
提出了一种用于不确定复杂网络轨迹跟踪的新方法。为实现这一目标，将神经控制器应用于一小部分节点（固定节点）。这种控制器由基于递归高阶神经网络的在线标识符和用于跟踪期望轨迹的逆最优控制器组成；还包括完整的稳定性分析。为了验证所提出控制方案的适用性和良好性能，对一个代表性示例进行了仿真，该示例由一个复杂网络组成，每个节点由混沌洛伦兹振荡器描述。
