Wang Xiangyu, Zheng Wei Xing, Wang Guodong
IEEE Trans Neural Netw Learn Syst. 2023 Sep;34(9):6042-6054. doi: 10.1109/TNNLS.2021.3132658. Epub 2023 Sep 1.
In this article, the distributed finite-time optimization problem is investigated for second-order multiagent systems with unknown velocities, disturbances, and quadratic local cost functions. To solve this problem, by combining finite-time observers (FTOs), the homogeneous systems theory, and distributed finite-time estimator techniques together, an output feedback-based feedforward-feedback composite distributed control scheme is proposed. Specifically, the control scheme consists of three parts. First, some FTOs are developed for the agents to estimate their unknown velocities and the disturbances together. Second, based on the velocity and disturbance estimates, the homogeneous system theory, and some global information on all the local cost functions' gradients, Hessian matrices, and the velocity estimates, a kind of centralized finite-time optimization controllers is designed. Third, by designing some distributed finite-time estimators and using their estimates to replace the global terms employed in the centralized optimization controllers, the distributed finite-time optimization controllers are derived. These controllers achieve the distributed finite-time optimization goal. Simulations illustrate the effectiveness and superiority of the proposed control scheme.
本文研究了具有未知速度、干扰和二次局部代价函数的二阶多智能体系统的分布式有限时间优化问题。为解决该问题，通过将有限时间观测器（FTO）、齐次系统理论和分布式有限时间估计技术相结合，提出了一种基于输出反馈的前馈-反馈复合分布式控制方案。具体而言，该控制方案由三部分组成。首先，为智能体开发了一些FTO，用于共同估计其未知速度和干扰。其次，基于速度和干扰估计、齐次系统理论以及所有局部代价函数梯度、海森矩阵和速度估计的一些全局信息，设计了一种集中式有限时间优化控制器。第三，通过设计一些分布式有限时间估计器，并利用它们的估计值替代集中式优化控制器中使用的全局项，推导出分布式有限时间优化控制器。这些控制器实现了分布式有限时间优化目标。仿真结果说明了所提控制方案的有效性和优越性。
