TY - JOUR
T1 - Spectral radius minimization for optimal average consensus and output feedback stabilization
AU - Kim, Yoonsoo
AU - Gu, Da-Wei
AU - Postlethwaite, Ian
PY - 2009/6
Y1 - 2009/6
N2 - In this paper, we consider two problems which can be posed as spectral radius minimization problems. Firstly, we consider the fastest average agreement problem on multi-agent networks adopting a linear information exchange protocol. Mathematically, this problem can be cast as finding an optimal such that x(k+1)=Wx(k), , and . Here, is the value possessed by the agents at the kth time step, is an all-one vector and is the set of real matrices in with zeros at the same positions specified by a network graph , where is the set of agents and is the set of communication links between agents. The optimal W is such that the spectral radius is minimized. To this end, we consider two numerical solution schemes: one using the qth-order spectral norm (2-norm) minimization (q-SNM) and the other gradient sampling (GS), inspired by the methods proposed in [Burke, J., Lewis, A., & Overton, M. (2002). Two numerical methods for optimizing matrix stability. Linear Algebra and its Applications, 351–352, 117–145; Xiao, L., & Boyd, S. (2004). Fast linear iterations for distributed averaging. Systems & Control Letters, 53(1), 65–78]. In this context, we theoretically show that when is symmetric, i.e. no information flow from the ith to the jth agent implies no information flow from the jth to the ith agent, the solution from the 1-SNM method can be chosen to be symmetric and is a local minimum of the function . Numerically, we show that the q-SNM method performs much better than the GS method when is not symmetric. Secondly, we consider the famous static output feedback stabilization problem, which is considered to be a hard problem (some think NP-hard): for a given linear system (A,B,C), find a stabilizing control gain K such that all the real parts of the eigenvalues of A+BKC are strictly negative. In spite of its computational complexity, we show numerically that q-SNM successfully yields stabilizing controllers for several benchmark problems with little effort.
AB - In this paper, we consider two problems which can be posed as spectral radius minimization problems. Firstly, we consider the fastest average agreement problem on multi-agent networks adopting a linear information exchange protocol. Mathematically, this problem can be cast as finding an optimal such that x(k+1)=Wx(k), , and . Here, is the value possessed by the agents at the kth time step, is an all-one vector and is the set of real matrices in with zeros at the same positions specified by a network graph , where is the set of agents and is the set of communication links between agents. The optimal W is such that the spectral radius is minimized. To this end, we consider two numerical solution schemes: one using the qth-order spectral norm (2-norm) minimization (q-SNM) and the other gradient sampling (GS), inspired by the methods proposed in [Burke, J., Lewis, A., & Overton, M. (2002). Two numerical methods for optimizing matrix stability. Linear Algebra and its Applications, 351–352, 117–145; Xiao, L., & Boyd, S. (2004). Fast linear iterations for distributed averaging. Systems & Control Letters, 53(1), 65–78]. In this context, we theoretically show that when is symmetric, i.e. no information flow from the ith to the jth agent implies no information flow from the jth to the ith agent, the solution from the 1-SNM method can be chosen to be symmetric and is a local minimum of the function . Numerically, we show that the q-SNM method performs much better than the GS method when is not symmetric. Secondly, we consider the famous static output feedback stabilization problem, which is considered to be a hard problem (some think NP-hard): for a given linear system (A,B,C), find a stabilizing control gain K such that all the real parts of the eigenvalues of A+BKC are strictly negative. In spite of its computational complexity, we show numerically that q-SNM successfully yields stabilizing controllers for several benchmark problems with little effort.
KW - distributed control
KW - communication networks
U2 - 10.1016/j.automatica.2009.02.001
DO - 10.1016/j.automatica.2009.02.001
M3 - Article
SN - 0005-1098
VL - 45
SP - 1379
EP - 1386
JO - Automatica
JF - Automatica
IS - 6
ER -