access icon free Convexified output-feedback consensus synthesis for linear multi-agent systems

© The Institution of Engineering and Technology
Received 08/05/2018, Accepted 29/03/2019, Revised 28/02/2019, Published 11/04/2019

This study addresses the consensus problem for linear multi-agent systems subject to external disturbances under the leaderless framework. A novel distributed dynamic output feedback control protocol is proposed, which utilises not only relative output information of neighbouring agents but also relative state information of neighbouring controllers. Through model transformation, the consensus control problem of multi-agents network is reduced to a set of independent stabilisation subproblems for n-dimensional linear systems. Sufficient analysis conditions are derived using the Lyapunov method. An important contribution of this work lies in that the leaderless output-feedback consensus synthesis conditions are convexified without introducing any conservatism and formulated as linear matrix inequalities, which can be solved efficiently via convex optimisation. This is achieved by using a novel dynamic output-feedback controller structure. A numerical example has been used to demonstrate the advantage of theoretical results.

Inspec keywords: multi-robot systems; control system synthesis; discrete time systems; linear systems; stability; multi-agent systems; distributed control; feedback; Lyapunov methods; linear matrix inequalities; time-varying systems

Other keywords: external disturbances; leaderless framework; relative output information; linear matrix inequalities; dynamic output feedback control protocol; dimensional linear systems; H∞ output-feedback consensus synthesis conditions; multiagent network; relative state information; dynamic output-feedback controller structure; sufficient analysis conditions; neighbouring controllers; linear multiagent systems subject

Subjects: Algebra; Stability in control theory; Multivariable control systems; Discrete control systems; Time-varying control systems; Nonlinear control systems; Combinatorial mathematics; Control system analysis and synthesis methods; Linear control systems

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