Adaptive leader‐following state consensus of multiagent systems with switching topology

Abstract

In this paper, an adaptive leader-following consensus problem of multiagent systems with possibly persistent switching topology is solved. The control goal is to achieve state consensus of multiagent systems with switching topology in the presence of system parameter uncertainties. After introducing an indicator function, a new uniform nominal controller structure is developed to ensure consensus for multiagent systems with switching topology for the case of known system parameters, which provides the a priori knowledge for the adaptive control design. Then, an adaptive state consensus control scheme is developed for dealing with unknown dynamics of both the leader and the followers, for multiagent systems with switching topology. Complete stability and asymptotic state consensus analysis is shown to guarantee the desired consensus performance despite possibly persistent topology switches. A simulation study with several different cases is conducted to evaluate the effectiveness of the proposed adaptive consensus control scheme. KEYWORDSadaptive control, multiagent system, piecewise constant parameters, state consensus, switching topology 1508

Saturated observer‐based adaptive neural network leader‐following control of N tractors with n‐trailers with a guaranteed performance

“…The coordinated tracking control of multiple mobile robots has attracted a great deal of attention during the recent decades due to their effective applications in rescue operations, autonomous exploration, intelligent transportation, surveillance, reconnaissance, coverage, and so on 1‐17 . Among many different coordinated control problems, one of the most popular methods is the leader‐following control due to its reliability, scalability, and simplicity 8‐10 where one or more followers try to preserve a desired distance and angle from a virtual or real vehicle which is called the leader.…”

“…Among many different coordinated control problems, one of the most popular methods is the leader‐following control due to its reliability, scalability, and simplicity 8‐10 where one or more followers try to preserve a desired distance and angle from a virtual or real vehicle which is called the leader. There exist many researches in the literature that address this problem for mobile robots 8‐17 . However, the most of them are devoted to differential‐drive robots.…”

“…Therefore, the coordinated control of multiple tractors with n ‐trailers greatly increases the capacity of the transportation in different applications including material collection, luggage carrier, crop harvesting, and logistic operations. Unfortunately, there does not exist any research effort that addresses the coordinated control of N tractors with n ‐trailers in the literature 1‐36 . In fact, the design of coordinated tracking controllers for these vehicles is very challenging due to their nonholonomic constraints, their multi‐body dynamics, and coupling effects between the tractor and consecutive trailers.…”

Adaptive cooperative tracking control of uncertain nonlinear multiagent systems with uncertain Markov switching communication graphs

“…3 Consensus, which is a fundamental problem of multiagent systems, has attracted a lot of attention in recent years. [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22] Different from the existing results on consensus, this paper focuses on the leader-following consensus problem of uncertain nonlinear multiagent systems with partly unknown Markovian switching signal, which is also called cooperative tracking problem. Our study is inspired by the following observations.…”

“…(2) Two distributed controllers are proposed to deal with the consensus problem of uncertain nonlinear multiagent systems with partly unknown switching topology. Compared with the controller in the existing works, where the exact parameters of individual agents 9,13,24 or precise switching signal 4,15,18,[34][35][36][37][38] were required, the controller designed in this paper has good adaptability and robustness. (3) The controllers proposed in this paper are not only based on state feedback but also based on the output feedback, which implies that the controllers proposed in this paper have broad application scenarios.…”