A Network Optimization Approach to Cooperative Control Synthesis

The mathematical theory of nonlinear cooperative control relies heavily on notions from graph theory and passivity theory. A general analysis result is known about cooperative control of maximally equilibrium-independent systems, relating steady-states of the closed-loop system to network optimization theory. However, until now only analysis results have been proven, and there is no known synthesis result. This letter presents a controller synthesis procedure for a class of diffusively coupled dynamic networks. We use tools from network optimization and convex analysis to show that for a network composed of maximally equilibrium independent passive systems, it is possible to construct controllers on the edges that are maximally equilibrium independent output-strictly passive and achieve any desired formation. Furthermore, we show that this can be achieved with linear controllers. We also provide a simple controller augmentation procedure to allow for reconfiguration of the desired output formation without a redesign of the nominal control. We then apply the presented methods to reconstruct the well-known consensus algorithm, and to study formation control in networks of damped oscillators.

[1]  Jordi Sabater-Mir,et al.  Reputation and social network analysis in multi-agent systems , 2002, AAMAS '02.

[2]  Mark W. Spong,et al.  Passivity-Based Control of Multi-Agent Systems , 2006 .

[3]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[4]  Mahmoud-Reza Haghifam,et al.  Load management using multi-agent systems in smart distribution network , 2013, 2013 IEEE Power & Energy Society General Meeting.

[5]  Arjan van der Schaft,et al.  Port-Hamiltonian Systems on Graphs , 2011, SIAM J. Control. Optim..

[6]  George H. Hines,et al.  Equilibrium-independent passivity: A new definition and numerical certification , 2011, Autom..

[7]  Miel Sharf,et al.  On Certain Properties of Convex Functions , 2017 .

[8]  D. Bertsekas Network Flows and Monotropic Optimization (R. T. Rockafellar) , 1985 .

[9]  Frank Allgöwer,et al.  Duality and network theory in passivity-based cooperative control , 2013, Autom..

[10]  Rodolphe Sepulchre,et al.  Analysis of Interconnected Oscillators by Dissipativity Theory , 2007, IEEE Transactions on Automatic Control.

[11]  Karl Henrik Johansson,et al.  Event-Triggered Pinning Control of Switching Networks , 2015, IEEE Transactions on Control of Network Systems.

[12]  R. Rockafellar Characterization of the subdifferentials of convex functions , 1966 .

[13]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[14]  Hyo-Sung Ahn,et al.  A survey of multi-agent formation control , 2015, Autom..

[15]  Eduardo D. Sontag,et al.  Synchronization of Interconnected Systems With Applications to Biochemical Networks: An Input-Output Approach , 2009, IEEE Transactions on Automatic Control.

[16]  Magnus Egerstedt,et al.  Graph Theoretic Methods in Multiagent Networks , 2010, Princeton Series in Applied Mathematics.

[17]  Albert-László Barabási,et al.  Controllability of complex networks , 2011, Nature.

[18]  M. Areak,et al.  Passivity as a design tool for group coordination , 2006, 2006 American Control Conference.

[19]  Antonio Franchi,et al.  A passivity-based decentralized approach for the bilateral teleoperation of a group of UAVs with switching topology , 2011, 2011 IEEE International Conference on Robotics and Automation.

[20]  John T. Wen,et al.  Cooperative Control Design - A Systematic, Passivity-Based Approach , 2011, Communications and control engineering.