Distributed position estimation approach for multiagent formation with size scaling

Abstract

This work studies formation control of multiagent systems (MASs) where its formation size is scalable via a scaling factor (scalable formation). Past works on scalable formation are limited to either fixed undirected graph or fixed directed graph with p-rooted graph condition. This work proposes a new distributed algorithm for scalable formation based on a distributed observer to estimate agents' positions. The new algorithm results in a new matrix, a Laplacian matrix with additional diagonal terms, where the desired formation pattern is embedded in this diagonal terms. With the proposed algorithm, only spanning tree condition is needed as the necessary and sufficient condition to achieve the scalable formation. Numerical examples are shown to illustrate the proposed method.

Investigation of the Implementation of Leader-Follower Formation Control to Bipedal Locomotion

“…While −𝐿𝐿 is Lyapunov stable with one zero eigenvalue, −𝐹𝐹 is stable [14]. Equation (10) then describe the leader -follower structure using consensus algorithm.…”

“…The formation control using leader-follower based structure, which based on consensus control algorithm, allows us to control several agents into formation and perform formation tracking [9], [10]. In this work, we investigate the use of consensus-based formation control algorithm to the inverted double pendulum model for biped locomotion purpose.…”

Finite‐time leader–follower consensus control of multiagent systems with mismatched disturbances

“…Recently, due to its wide and practical applications, cooperative controls of multiagent systems (MASs) have gained more and more interest from researchers of control communities [1][2][3]. A group of networked agents can complete a difficult task quickly and flexibly by using local relative information [4].…”

Scalable multi‐agent formation control under switching leader–follower directed graph

“…While Lin et al [14] allows for negative communication weight, Han et al [15] uses complex‐valued communication weight. The work by Djamari [16] solves scalable formation of single integrator and double integrator agents under fixed communication network; and similar to Lin et al [14] and Han et al [15], the work by Djamari [16] designs the communication weight according to the desired formation. However, the work by Djamari [16] uses real‐numbered communication weight, and it can work in any dimension.…”

“…In this example, agents scale-down the formation size when they need to pass a narrow path, and scale-back the formation size once they pass the narrow path. This type of formation control problem is called as scalable formation (see the works [11][12][13][14][15][16]).…”