Abstract
This study considers the problem of formation control for second-order multiagent systems. We propose a distributed nonlinear formation controller where the control input of each follower can be expressed as a product of a nonlinear term that relies on the distance errors under the leader–follower structure. In the leader–follower structure, a small number of agents are assumed to be the leaders, and they are responsible for steering a group of agents to the specific destination, while the rest of the agents are called followers. The stability of the proposed control laws is demonstrated by utilizing the Lyapunov function candidate. To solve the obstacle avoidance problem, the artificial potential approach is employed, and the agents can avoid each possible obstacle successfully without getting stuck in any local minimum point. The control problem of multiagent systems in the presence of unknown constant disturbances is also considered. To attenuate such disturbances, the integral term is introduced, and the static error is eliminated through the proposed PI controller, which makes the system stable; the adaptive controller is designed to reduce the effect of time-varying disturbances. Finally, numerical simulation results are presented to support the obtained theoretical results.
Highlights
Distributed or decentralized coordination control of multiagent systems has received increasing research attention in the control community; it has been widely used in many practical applications, such as unmanned surface vessels, unmanned aerial vehicles, satellite clusters, and military surveillance [1,2,3,4,5,6,7]
This study considers the problem of formation control for second-order multiagent systems
We propose a distributed nonlinear formation controller where the control input of each follower can be expressed as a product of a nonlinear term that relies on the distance errors under the leader–follower structure
Summary
Distributed or decentralized coordination control of multiagent systems has received increasing research attention in the control community; it has been widely used in many practical applications, such as unmanned surface vessels, unmanned aerial vehicles, satellite clusters, and military surveillance [1,2,3,4,5,6,7]. Two methods are considered for the formation control of multiagent systems, namely, the centralized [11] and decentralized controllers [12, 13], according to the interaction topology of sensing graph. Each agent is assumed to have access to all the states collected from the central controller. This controller may fail to achieve the control objective in the presence of faults. Each agent can achieve its own tasks defined according to the desired formation only based on the local measurements, which might provide reliable control when communication between agents is limited or even unavailable [14]. The decentralized controller devised for each agent under the leader–follower structure
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