Distributed Control of Networked Dynamical Systems: Static Feedback, Integral Action and Consensus

This paper analyzes distributed control protocols for first- and second-order networked dynamical systems. We propose a class of nonlinear consensus controllers where the input of each agent can be written as a product of a nonlinear gain, and a sum of nonlinear interaction functions. By using integral Lyapunov functions, we prove the stability of the proposed control protocols, and explicitly characterize the equilibrium set. We also propose a distributed proportional-integral (PI) controller for networked dynamical systems. The PI controllers successfully attenuate constant disturbances in the network. We prove that agents with single-integrator dynamics are stable for any integral gain, and give an explicit tight upper bound on the integral gain for when the system is stable for agents with double-integrator dynamics. Throughout the paper we highlight some possible applications of the proposed controllers by realistic simulations of autonomous satellites, power systems and building temperature control.

[1]  Evanghelos Zafiriou,et al.  Robust process control , 1987 .

[2]  Luc Moreau,et al.  Stability of multiagent systems with time-dependent communication links , 2005, IEEE Transactions on Automatic Control.

[3]  R. Murray,et al.  Consensus protocols for networks of dynamic agents , 2003, Proceedings of the 2003 American Control Conference, 2003..

[4]  Yang Liu,et al.  Stability analysis of M-dimensional asynchronous swarms with a fixed communication topology , 2003, IEEE Trans. Autom. Control..

[5]  Jorge Cortés,et al.  Analysis and design of distributed algorithms for χ-consensus , 2006 .

[6]  Karl Henrik Johansson,et al.  Distributed fault detection for interconnected second-order systems , 2011, Autom..

[7]  Fu Lin,et al.  Optimal Control of Vehicular Formations With Nearest Neighbor Interactions , 2011, IEEE Transactions on Automatic Control.

[8]  Guangming Xie,et al.  Consensus control for a class of networks of dynamic agents , 2007 .

[9]  Amir G. Aghdam,et al.  Sufficient conditions for the convergence of a class of nonlinear distributed consensus algorithms , 2011, Autom..

[10]  Laura Giarré,et al.  Non-linear protocols for optimal distributed consensus in networks of dynamic agents , 2006, Syst. Control. Lett..

[11]  Francesco Bullo,et al.  Distributed Control of Robotic Networks , 2009 .

[12]  Magnus Egerstedt,et al.  Control of multiagent systems under persistent disturbances , 2012, 2012 American Control Conference (ACC).

[13]  Guodong Shi,et al.  Global target aggregation and state agreement of nonlinear multi-agent systems with switching topologies , 2009, Autom..

[14]  Dimos V. Dimarogonas,et al.  Connectedness Preserving Distributed Swarm Aggregation for Multiple Kinematic Robots , 2008, IEEE Transactions on Robotics.

[15]  Mehran Mesbahi,et al.  Edge Agreement: Graph-Theoretic Performance Bounds and Passivity Analysis , 2011, IEEE Transactions on Automatic Control.

[16]  J. Cortes Analysis and design of distributed algorithms for X-consensus , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[17]  Dan Zhou,et al.  Review on thermal energy storage with phase change materials (PCMs) in building applications , 2012 .

[18]  A. Abdel-azim Fundamentals of Heat and Mass Transfer , 2011 .

[19]  N. Senroy,et al.  Decision Tree Assisted Controlled Islanding , 2006, IEEE Transactions on Power Systems.

[20]  Daizhan Cheng,et al.  Lyapunov-Based Approach to Multiagent Systems With Switching Jointly Connected Interconnection , 2007, IEEE Transactions on Automatic Control.

[21]  Luisa F. Cabeza,et al.  Review on thermal energy storage with phase change: materials, heat transfer analysis and applications , 2003 .

[22]  Karl Henrik Johansson,et al.  Undamped nonlinear consensus using integral Lyapunov functions , 2012, 2012 American Control Conference (ACC).

[23]  Janusz Bialek,et al.  Power System Dynamics: Stability and Control , 2008 .

[24]  Richard M. Murray,et al.  Information flow and cooperative control of vehicle formations , 2004, IEEE Transactions on Automatic Control.

[25]  Peng Yang,et al.  Stability and Convergence Properties of Dynamic Average Consensus Estimators , 2006, Proceedings of the 45th IEEE Conference on Decision and Control.

[26]  Naomi Ehrich Leonard,et al.  Robustness of noisy consensus dynamics with directed communication , 2010, Proceedings of the 2010 American Control Conference.

[27]  Frank Allgöwer,et al.  Robust Consensus Controller Design for Nonlinear Relative Degree Two Multi-Agent Systems With Communication Constraints , 2011, IEEE Transactions on Automatic Control.

[28]  Jorge Cortes,et al.  Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms , 2009 .

[29]  Frank P. Incropera,et al.  Fundamentals of Heat and Mass Transfer , 1981 .

[30]  Xiaoming Hu,et al.  An Extension of LaSalle's Invariance Principle and Its Application to Multi-Agent Consensus , 2008, IEEE Transactions on Automatic Control.

[31]  Rich Christie,et al.  30 Bus Power Flow Test Case , 1993 .

[32]  Randal W. Beard,et al.  Distributed Consensus in Multi-vehicle Cooperative Control - Theory and Applications , 2007, Communications and Control Engineering.

[33]  Bassam Bamieh,et al.  Coherence in Large-Scale Networks: Dimension-Dependent Limitations of Local Feedback , 2011, IEEE Transactions on Automatic Control.

[34]  A.G. Phadke,et al.  Synchronized phasor measurements in power systems , 1993, IEEE Computer Applications in Power.

[35]  Stephen P. Boyd,et al.  Distributed average consensus with least-mean-square deviation , 2007, J. Parallel Distributed Comput..

[36]  Karl Henrik Johansson,et al.  Distributed integral action: Stability analysis and frequency control of power systems , 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

[37]  Florian Dörfler,et al.  On the Critical Coupling for Kuramoto Oscillators , 2010, SIAM J. Appl. Dyn. Syst..