Distributed MPC Via Dual Decomposition and Alterna

Authors: F Farokhi I Shames K H Johansson

Publish Date: 2014

Volume: , Issue: , Pages: 115-131

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Abstract

A conventional way to handle model predictive control MPC problems distributedly is to solve them via dual decomposition and gradient ascent However at each timestep it might not be feasible to wait for the dual algorithm to converge As a result the algorithm might be needed to be terminated prematurely One is then interested to see if the solution at the point of termination is close to the optimal solution and when one should terminate the algorithm if a certain distance to optimality is to be guaranteed In this chapter we look at this problem for distributed systems under general dynamical and performance couplings then we make a statement on validity of similar results where the problem is solved using alternative direction method of multipliers

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