This paper presents a novel flocking algorithm based on a memory-enhanced disturbance observer.To compensate for external disturbances,a filtered regressor for the double integrator model subject to external disturban...This paper presents a novel flocking algorithm based on a memory-enhanced disturbance observer.To compensate for external disturbances,a filtered regressor for the double integrator model subject to external disturbances is designed to extract the disturbance information.With the filtered regressor method,the algorithm has the advantage of eliminating the need for acceleration information,thus reducing the sensor requirements in applications.Using the information obtained from the filtered regressor,a batch of stored data is used to design an adaptive disturbance observer,ensuring that the estimated values of the parameters of the disturbance system equation and the initial value converge to their actual values.The result is that the flocking algorithm can compensate for external disturbances and drive agents to achieve the desired collective behavior,including virtual leader tracking,inter-distance keeping,and collision avoidance.Numerical simulations verify the effectiveness of the algorithm proposed in the present study.展开更多
This paper addresses the distance-based formation tracking problem for a double-integrator modeled multi-agent system（MAS） in the presence of a moving leader in d-dimensional space. Under the assumption that the sta...This paper addresses the distance-based formation tracking problem for a double-integrator modeled multi-agent system（MAS） in the presence of a moving leader in d-dimensional space. Under the assumption that the state of leader can be obtained over fixed graphs, a distributed distance-based control protocol is designed for each double-integrator follower agent. The protocol consists of three terms： a gradient function term, a velocity consensus term, and a leader tracking term.Different shape stabilizing functions proposed in the literature can be applied to the gradient function term. The proposed controller allows all agents to both achieve the desired shape and reach the same velocity with moving leader by controlling the distances and velocity. Finally, we analyze the local asymptotic stability of the equilibrium set with center manifold theory. We validate the effectiveness of our approach through two examples.展开更多
文摘This paper presents a novel flocking algorithm based on a memory-enhanced disturbance observer.To compensate for external disturbances,a filtered regressor for the double integrator model subject to external disturbances is designed to extract the disturbance information.With the filtered regressor method,the algorithm has the advantage of eliminating the need for acceleration information,thus reducing the sensor requirements in applications.Using the information obtained from the filtered regressor,a batch of stored data is used to design an adaptive disturbance observer,ensuring that the estimated values of the parameters of the disturbance system equation and the initial value converge to their actual values.The result is that the flocking algorithm can compensate for external disturbances and drive agents to achieve the desired collective behavior,including virtual leader tracking,inter-distance keeping,and collision avoidance.Numerical simulations verify the effectiveness of the algorithm proposed in the present study.
基金supported by the National Natural Science Foundation of China(Grant No.61603188)
文摘This paper addresses the distance-based formation tracking problem for a double-integrator modeled multi-agent system（MAS） in the presence of a moving leader in d-dimensional space. Under the assumption that the state of leader can be obtained over fixed graphs, a distributed distance-based control protocol is designed for each double-integrator follower agent. The protocol consists of three terms： a gradient function term, a velocity consensus term, and a leader tracking term.Different shape stabilizing functions proposed in the literature can be applied to the gradient function term. The proposed controller allows all agents to both achieve the desired shape and reach the same velocity with moving leader by controlling the distances and velocity. Finally, we analyze the local asymptotic stability of the equilibrium set with center manifold theory. We validate the effectiveness of our approach through two examples.
