IEEE Trans Cybern. 2023 Jul;53(7):4189-4203. doi: 10.1109/TCYB.2022.3150032. Epub 2023 Jun 15.
This article proposes an adaptive robust formation control scheme for the connected and autonomous vehicle (CAV) swarm system by utilizing swarm property, diffeomorphism transformation, and constraint following. The control design is processed by starting from a 2-D dynamics model with (possibly fast) time varying but bounded uncertainty. The uncertainty bounds are unknown. For compact formation, the CAV system is treated as an artificial swarm system, for which the ideal swarm performance is taken as a desired constraint. By this, formation control is converted into a problem of constraint following and then a performance measure β is defined as the control object to evaluate the constraint following error. For collision avoidance, a diffeomorphism transformation on space measure between two vehicles is creatively performed, by which the space measure is positive restricted. For uncertainty handling, an adaptive robust control scheme is proposed to render the β -measure to be uniformly bounded and uniformly ultimately bounded, that is, drive the controlled (CAV) swarm system to follow the desired constraint approximatively. As a result, the system can achieve the ideal swarm performance; thereout, compact formation is realized, regardless of the uncertainty. The main contribution of this article is exploring a 2-D formation control scheme for (CAV) swarm system under the consideration of collision avoidance and time-varying uncertainty.
本文提出了一种基于群体特性、微分同胚变换和约束跟踪的自适应鲁棒编队控制方案，用于连接和自主车辆（CAV）群体系统。控制设计从具有（可能快速）时变但有界不确定性的 2-D 动力学模型开始。不确定性界限未知。对于紧凑编队，CAV 系统被视为人工群体系统，其理想群体性能被视为期望约束。通过这种方式，编队控制被转化为约束跟踪问题，然后定义性能度量β作为评估约束跟踪误差的控制目标。为了避免碰撞，创造性地对两个车辆之间的空间度量进行微分同胚变换，通过这种变换将空间度量进行正限制。为了处理不确定性，提出了一种自适应鲁棒控制方案，使β度量保持一致有界和一致最终有界，即，使受控（CAV）群体系统近似地遵循期望约束。结果，系统可以实现理想的群体性能；从而，实现了紧凑编队，而无需考虑不确定性。本文的主要贡献在于探索了在考虑避碰和时变不确定性的情况下，用于（CAV）群体系统的 2-D 编队控制方案。
