Active disturbance rejection based formation tracking and collision avoidance control for second-order multi-agent system
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摘要:
在多智能体编队的目标跟踪任务中，智能体受环境中的障碍物的遮挡作用会丢失目标，而外部扰动会影响系统的时变编队跟踪的控制效果。为此，研究了这两种因素同时存在情况下的二阶多智能体系统时变编队跟踪和避撞控制。采用基于目标跟踪优先级的切换拓扑控制策略以实现在障碍物遮挡环境中对目标的持续跟踪，根据自抗扰理论设计包含扰动补偿项的编队跟踪控制器。首先，基于一致性方法提出切换拓扑下自抗扰时变编队跟踪控制协议，并给出一种基于跟踪微分器的编队指令生成方法；其次，设计了求解控制参数的算法并给出协议作用下系统的稳定性分析和证明；然后，基于人工势场法设计避撞控制协议；最后，提出障碍物遮挡环境下自抗扰时变编队跟踪控制协议。仿真实验结果表明：所设计的控制协议在上述两种因素存在时仍具有良好的控制效果。
Abstract:In target tracking task for multi-agent formation, the agent will lose the target when it is blocked by obstacles in the environment and external disturbances can affect the time-varying formation tracking control for multi-agent systems. This paper studies the time-varying formation tracking and collision avoidance control for second-order multi-agent systems under the simultaneous existence of these two factors. A switching topology control strategy based on target tracking priority is adopted to achieve continuous tracking of the target in the obstacle occlusion environment. A formation tracking controller including the disturbance compensation term is designed based on active disturbance rejection theory. First, an active disturbance rejection time-varying formation target tracking control protocol is proposed for multi-agent systems with switching topologies based on consensus methods, and a formation command generation method based on tracking differentiator is presented. Then, an algorithm is designed to determine the control coefficient matrix, and the stability of the system under the protocol is analyzed and proved. Moreover, a collision avoidance control protocol is designed based on artificial potential field method. Finally, the active disturbance rejection time-varying formation target tracking and collision avoidance control protocol is proposed considering the occlusion of target tracking by obstacles in the environment. The simulation results show that the control protocol designed in this paper still has good control effect when the above two factors exist.
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图 4 实验1-1中无人机与目标位置轨迹
Figure 4. Position trajectories of UAVs and target in experiment 1-1
图 5 实验1-1中无人机与目标高度差曲线
Figure 5. Curves of altitude difference between UAVs and target in experiment 1-1
图 6 实验1-1中无人机与障碍物距离曲线
Figure 6. Curves of distance between UAVs and obstacles in experiment 1-1
图 8 实验1-2中无人机与目标位置轨迹
Figure 8. Position trajectories of UAVs and target in experiment 1-2
图 9 实验1-2中无人机与目标高度差曲线
Figure 9. Curves of altitude difference between UAVs and target in experiment 1-2
图 10 实验1-2中无人机与障碍物距离曲线
Figure 10. Curves of distance between UAVs and obstacles in experiment 1-2
图 13 实验2-1中无人机与目标位置轨迹
Figure 13. Position trajectories of UAVs and target in experiment 2-1
图 14 实验2-1中无人机与目标高度差曲线
Figure 14. Curves of altitude difference between UAVs and target in experiment 2-1
图 18 实验2-2中无人机与目标位置轨迹
Figure 18. Position trajectories of UAVs and target in experiment 2-2
图 19 实验2-2中无人机与目标高度差曲线
Figure 19. Curves of altitude difference between UAVs and the target in experiment 2-2
图 15 实验2-1中无人机与障碍物距离曲线
Figure 15. Curves of distance between UAVs and obstacles in experiment 2-1
图 17 实验2-1中作用拓扑切换过程
Figure 17. Switching process of interaction topologies in experiment 2-1
图 20 实验2-2中无人机与障碍物距离曲线
Figure 20. Curves of distance between UAVs and obstacles in experiment 2-2
图 22 实验2-2中作用拓扑切换过程
Figure 22. Switching process of interaction topologies in experiment 2-2
表 1 目标和无人机的初始状态向量
Table 1. Initial state vectors of target and UAVs
智能体 位置向量/m 速度向量/(m·s-1) 目标 (0, 0, 0) (0, 0, 0.1) 2号无人机 (0, 6, 0) (0, 0, 0) 3号无人机 
(0, 0, 0) 4号无人机 
(0, 0, 0) 
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表 2 障碍物位置向量
Table 2. Position vectors of obstacles
实体类障碍物 位置向量/m 1号障碍物 (0, －6, 1) 2号障碍物 
3号障碍物 
4号障碍物 (0, －6, 11) 5号障碍物 
6号障碍物 
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表 3 作用拓扑的切换规则
Table 3. Switching rule of interaction topologies
障碍物对无人机的遮挡情况 通信拓扑 2号无人机未被遮挡，其他无人机被遮挡或未被遮挡 A 2号无人机被遮挡，3号无人机未被遮挡，4号无人机被遮挡或未被遮挡 B 2号和3号无人机均被遮挡，4号无人机未被遮挡 C
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