A primal‐dual active‐set method for distributed model predictive control

Abstract

Summary We present a novel distributed primal‐dual active‐set method for model predictive control. The primal‐dual active‐set method is used for solving model predictive control problems for large‐scale systems with quadratic cost, linear dynamics, additive disturbance, and box constraints. The proposed algorithm is compared with dual decomposition and an alternating direction method of multipliers. Theoretical and experimental results show the effectiveness of the proposed approach for large‐scale systems with communication delays. The application to building control systems is thoroughly investigated. Copyright © 2016 John Wiley & Sons, Ltd.

A Fast Strategy for Model Predictive Control

“…•Using the improved online and explicit MPC methods (active set, interior point, and multi-parametric solvers) [7][8][9][10][11][12][13][14][15][16][17][18][19],…”

“…When the free times are not used for the improvement of MPC algorithms, UMPC has energy efficiency according to the original MPC. The method can be applied to the MPC methods [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22], and extended to nonlinear plant models. In the study, the main idea of the method and its application results on a simulation are discussed.…”

Distributed model predictive control for building energy systems in distribution grids

“…An efficient solution is to distribute the computational requirements over multiple units, but this can lead to high communication costs. Building on the work of [19], [20], we propose a distributed MPC control framework that integrates and optimally coordinates demand response, onsite generation and energy storage. By doing so the building will be able to offer ancillary services to the grid operator without violating indoor comfort.…”

“…However, differently from traditional active-set methods, it exhibits significant improved convergence rates with local superlinear convergence. This is particular beneficial for large-scale control problems with communication delays, as building control applications [20]. The authors in [20] show that the algorithm described in [19] is implementable in a distributed fashion and can overcome also the aforementioned shortcoming of high communication costs.…”

“…This is particular beneficial for large-scale control problems with communication delays, as building control applications [20]. The authors in [20] show that the algorithm described in [19] is implementable in a distributed fashion and can overcome also the aforementioned shortcoming of high communication costs. The application to building temperature control is thoroughly investigated: theoretical and experimental results demonstrate that the distributed implementation of the active-set method in [19] outperforms dual decomposition and ADMM especially in building control applications, requiring much smaller number of iterations to converge and significantly reducing the computation time.…”