Distributed Neuro-Adaptive Prescribed Performance Consensus Control for Nontriangular Structural Multiagent Systems
针对一类非三角结构的多智能体系统，提出了一种神经自适应预设性能一致性控制方案，利用均值定理和神经网络重构系统模型，确保跟随者以预定速度同步且误差在规定时间内收敛到指定范围。
For a class of nontriangular structural multiagent systems, this article presents a neuro-adaptive prescribed performance consensus control scheme. By using mean value theorem to isolate the virtual variables and neural networks to approximate the ideal controller, the system model is reconstructed, based on which the virtual controllers are able to be derived. The algebraic-loop problem is circumvented utilizing the properties of basis function. With the proposed performance functions, an error transformation is presented, based on which the controller scheme is developed. It is ensured that the follower agents synchronize at a predefined speed, and synchronization error converges to a specified range within a given time. Two Simulations demonstrate the effectiveness of the presented control method.