Distributed Algorithm for Controllability Test of Discrete-time Linear Systems

This paper investigates the problem to test the controllability of large-scale discrete-time linear systems in a distributed way. The controllability Gramian is the solution of a discrete-time Lyapunov equation. All agents in the large-scale network system solve the discrete-time Lyapunov equation by exchange information with their neighbors. Every agent of the network has access to partial information of the system and has two dynamic estimation variables. A distributed discrete-time algorithm with a constant step size is proposed and a numerical simulation is carried out to verify the convergence property.

[1]  Robert A. Beezer Archetype Summary to accompany A First Course in Linear Algebra , 2006 .

[2]  Peter Benner,et al.  Numerical solution of large‐scale Lyapunov equations, Riccati equations, and linear‐quadratic optimal control problems , 2008, Numer. Linear Algebra Appl..

[3]  João Pedro Hespanha,et al.  Linear Systems Theory , 2009 .

[4]  Asuman E. Ozdaglar,et al.  Constrained Consensus and Optimization in Multi-Agent Networks , 2008, IEEE Transactions on Automatic Control.

[5]  Wen-Wei Lin,et al.  Large-scale Stein and Lyapunov equations, Smith method, and applications , 2013, Numerical Algorithms.

[6]  M. Sadkane A low-rank Krylov squared Smith method for large-scale discrete-time Lyapunov equations , 2012 .

[7]  Martin J. Wainwright,et al.  Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling , 2010, IEEE Transactions on Automatic Control.

[8]  Karl Henrik Johansson,et al.  Randomized optimal consensus of multi-agent systems , 2011, Autom..

[9]  Feng Liu,et al.  Distributed gradient algorithm for constrained optimization with application to load sharing in power systems , 2015, Syst. Control. Lett..

[10]  Shaoshuai Mou,et al.  A Distributed Algorithm for Solving a Linear Algebraic Equation , 2013, IEEE Transactions on Automatic Control.

[11]  Shaoshuai Mou,et al.  Decentralized gradient algorithm for solution of a linear equation , 2015, ArXiv.

[12]  Xing Zhang,et al.  Coordination Between Unmanned Aerial and Ground Vehicles: A Taxonomy and Optimization Perspective , 2016, IEEE Transactions on Cybernetics.

[13]  Xiaoyu Liu,et al.  Consensus for networked multi-agent systems with unknown communication delays , 2016, J. Frankl. Inst..

[14]  Shengyuan Xu,et al.  Regularized Primal–Dual Subgradient Method for Distributed Constrained Optimization , 2016, IEEE Transactions on Cybernetics.

[15]  Kai Cao,et al.  Computation of linear algebraic equations with solvability verification over multi-agent networks , 2017, Kybernetika.

[16]  Ji Liu,et al.  Exponential convergence of a distributed algorithm for solving linear algebraic equations , 2017, Autom..

[17]  Jie Chen,et al.  An optimization-based shared control framework with applications in multi-robot systems , 2017, Science China Information Sciences.

[18]  Brian D. O. Anderson,et al.  Network Flows That Solve Linear Equations , 2015, IEEE Transactions on Automatic Control.

[19]  Lu Liu,et al.  Consensus of linear multi‐agent systems subject to communication delays and switching networks , 2017 .

[20]  Yiguang Hong,et al.  Distributed Continuous-Time Algorithm for Constrained Convex Optimizations via Nonsmooth Analysis Approach , 2015, IEEE Transactions on Automatic Control.

[21]  Zhong-Ping Jiang,et al.  Distributed Global Output-Feedback Control for a Class of Euler–Lagrange Systems , 2017, IEEE Transactions on Automatic Control.

[22]  Long Wang,et al.  Controllability analysis of multi-agent systems with switching topology over finite fields , 2018, Science China Information Sciences.

[23]  Jian Sun,et al.  Distributed Algorithm for Discrete-Time Lyapunov Equations , 2018, 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV).

[24]  Xuan Zhang,et al.  Distributed Control for Reaching Optimal Steady State in Network Systems: An Optimization Approach , 2018, IEEE Transactions on Automatic Control.

[25]  Jie Chen,et al.  Cooperative transportation control of multiple mobile manipulators through distributed optimization , 2018, Science China Information Sciences.

[26]  Shaoyuan Li,et al.  On strong structural controllability and observability of linear time-varying systems: a constructive method , 2018, Science China Information Sciences.

[27]  Shaoshuai Mou,et al.  Asynchronous Distributed Algorithms for Solving Linear Algebraic Equations , 2018, IEEE Transactions on Automatic Control.

[28]  Daniel W. C. Ho,et al.  An Adaptive Primal-Dual Subgradient Algorithm for Online Distributed Constrained Optimization , 2018, IEEE Transactions on Cybernetics.

[29]  Lean Yu,et al.  Privacy Preservation in Distributed Subgradient Optimization Algorithms , 2015, IEEE Transactions on Cybernetics.

[30]  Tamer Basar,et al.  Distributed discrete-time optimization by exchanging one bit of information , 2017, 2018 Annual American Control Conference (ACC).

[31]  Shu Liang,et al.  Distributed Computation of Linear Matrix Equations: An Optimization Perspective , 2017, IEEE Transactions on Automatic Control.