动态事件触发机制下多智能体系统固定时间跟踪

doi:10.12382/bgxb.2022.1267

摘要/Abstract

摘要：

针对受扰非线性多智能体系统跟踪控制问题,提出一种基于动态事件触发机制的固定时间积分滑模控制方法。设计与相对状态信息相关的新型积分滑模面且提出分布式控制协议,基于测量误差和滑模面构造动态变量和动态事件触发函数。采用固定时间稳定性原理证明,若选取适当的控制参数则可使多智能体系统在固定时间内实现动态事件触发机制下的跟踪控制,且避免Zeno现象。该控制方案能够有效抑制系统扰动的影响,减少多智能体系统通信和计算资源的消耗,且避免收敛时间对系统初始状态的依赖。仿真结果表明,新提出的动态事件触发控制器使得多智能体系统在固定时间内实现跟踪控制,降低触发频率而节省资源,更适用于实际应用。

关键词: 多智能体系统, 动态事件触发机制, 固定时间控制, 积分滑模

Abstract:

To solve the tracking control problem of disturbed nonlinear multi-agent system, a fixed-time integral sliding mode control method is proposed based on dynamic event triggering mechanism. A new integral sliding mode surface is designed based on relative state information, the distributed control protocol is developed, and dynamic variable and dynamic event triggering mechanism are constructed on the basis of the measurement error and the sliding mode surface. It can be proved that the appropriate selection of control parameters can drive the multi-agent system to achieve trajectory tracking within a fixed time under the dynamic event triggering mechanism with Zeno behavior avoided. The proposed control scheme can effectively suppress the influence of system disturbance and reduce the consumption of communication and computing resources of the multi-agent system, and meanwhile, avoid the dependence of the convergence time on the initial states of the system. The simulation results demonstrate that the proposed dynamic event triggering controller allows the multi-agent system to achieve the tracking control in fixed time and reduce the triggering frequency to save resources, which is more suitable for practical applications.

Key words: multi-agent systems, dynamic event triggering mechanism, fixed-time control, integral sliding mode

于镝, 王亚洁, 赵博, 刘琼. 动态事件触发机制下多智能体系统固定时间跟踪[J]. 兵工学报, 2023, 44(5): 1403-1413.

YU Di, WANG Yajie, ZHAO Bo, LIU Qiong. Fixed-Time Tracking Control of Multi-agent Systems under Dynamic Event-Triggering Mechanism[J]. Acta Armamentarii, 2023, 44(5): 1403-1413.

图/表 11

图1 控制方案示意图

Fig.1 Diagram of control scheme

图2 网络拓扑

Fig.2 Network topology

图3 智能体位置变化轨迹

Fig.3 Position trajectories of agents

图4 智能体速度变化轨迹

Fig.4 Velocity trajectories of agents

图5 动态辅助变量变化曲线

Fig.5 Curves of dynamic auxiliary variables

图6 误差和触发阈值的变化曲线

Fig.6 Curves of errors and trigger threshold

图7 较大初始值下智能体位置轨迹

Fig.7 Position trajectories of agents with large initial values

图8 较大初始值下智能体速度轨迹

Fig.8 Velocity trajectories of agents with large initial values

图9 动态事件触发机制下智能体触发时刻

Fig.9 Trigger time of agents under the dynamic triggering mechanism

图10 静态触发机制下智能体触发时刻

Fig.10 Trigger time of agents under the static triggering mechanism

表1 动态触发机制与静态触发机制次数比较

Table 1 Comparison of triggering frequency of the dynamic and static triggering mechanisms

动态触发和静态触发	智能体
动态触发和静态触发	1	2	3	4	5
动态触发	179	159	148	191	206
静态触发	5129	5190	5191	5229	5208

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