Distributed Synthesis Using Accelerated ADMM
Abstract
We propose a convex distributed optimization algorithm for synthesizing robust controllers for largescale continuous time systems subject to exogenous disturbances. Given a large scale system, instead of solving the larger centralized synthesis task, we decompose the problem into a set of smaller synthesis problems for the local subsystems with a given interconnection topology. Hence, the synthesis problem is constrained to the sparsity pattern dictated by the interconnection topology. To this end, for each subsystem, we solve a local dissipation inequality and then check a smallgain like condition for the overall system. To minimize the effect of disturbances, we consider the $\mathrm{H}_\infty$ synthesis problems. We instantiate the distributed synthesis method using accelerated alternating direction method of multipliers (ADMM) with convergence rate $O(\frac{1}{k^2})$ with $k$ being the number of iterations.
 Publication:

arXiv eprints
 Pub Date:
 February 2018
 arXiv:
 arXiv:1803.00077
 Bibcode:
 2018arXiv180300077A
 Keywords:

 Mathematics  Optimization and Control
 EPrint:
 To appear in ACC 2018