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Distributed Containment Control for Multiple Autonomous Vehicles With Double-Integrator Dynamics: Algorithms and Experiments

机译:具有双积分动力学的多辆无人驾驶汽车的分布式遏制控制:算法和实验

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This brief studies distributed containment control for double-integrator dynamics in the presence of both stationary and dynamic leaders. In the case of stationary leaders, we propose a distributed containment control algorithm and study conditions on the network topology and the control gains to guarantee asymptotic containment control in any dimensional space. In the case of dynamic leaders, we study two cases: leaders with an identical velocity and leaders with nonidentical velocities. For the first case, we propose two distributed containment control algorithms to solve, respectively, asymptotic containment control under a switching directed network topology and finite-time containment control under a fixed directed network topology. In particular, asymptotic containment control can be achieved for any dimensional space if the network topology is fixed and for only the 1-D space if the network topology is switching. For the second case, we propose a distributed containment control algorithm under a fixed network topology where the communication patterns among the followers are undirected and derive conditions on the network topology and the control gains to guarantee asymptotic containment control for any dimensional space. Both simulation results and experimental results on a multi-robot platform are provided to validate some theoretical results.
机译:这项简短的研究在静态和动态领导者的存在下,针对双积分器动力学进行了分布式控制。在固定领导者的情况下,我们提出了一种分布式安全壳控制算法,并研究了网络拓扑和控制增益的条件,以保证在任何维空间中的渐近安全壳控制。对于动态领导者,我们研究了两种情况:速度相同的领导者和速度不同的领导者。对于第一种情况,我们提出了两种分布式安全壳控制算法,分别解决切换有向网络拓扑下的渐近安全壳控制和固定有向网络拓扑下的有限时间安全壳控制。特别地,如果网络拓扑是固定的,则对于任何维空间都可以实现渐进包容性控制;如果网络拓扑是交换的,则只能实现一维空间。对于第二种情况,我们提出了一种固定网络拓扑结构下的分布式遏制控制算法,其中跟随者之间的通信模式是无向的,并推导了网络拓扑结构的条件和控制增益,以保证对任何维空间的渐近遏制控制。提供了在多机器人平台上的仿真结果和实验结果,以验证一些理论结果。

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