scholarly journals Accelerated gradient methods and dual decomposition in distributed model predictive control

Automatica ◽  
2013 ◽  
Vol 49 (3) ◽  
pp. 829-833 ◽  
Author(s):  
Pontus Giselsson ◽  
Minh Dang Doan ◽  
Tamás Keviczky ◽  
Bart De Schutter ◽  
Anders Rantzer
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Gradient Methods ◽  
Distributed Model ◽  
Dual Decomposition ◽  
Distributed Model Predictive Control ◽  
Accelerated Gradient ◽  
Accelerated Gradient Methods

Nonlinear distributed model predictive control with dual decomposition and event-based communication approach

2020 ◽  
Vol 42 (15) ◽  
pp. 2929-2940 ◽  
Author(s):  
Dine El Houda Hammami ◽  
Saber Maraoui ◽  
Kais Bouzrara
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Communication Strategy ◽  
Distributed Model ◽  
Communication Constraints ◽  
Dual Decomposition ◽  
Distributed Model Predictive Control ◽  
Accelerated Gradient ◽  
Communication Approach ◽  
Event Based

This paper proposes a dual decomposition method for solving distributed model predictive control. This controller is designed for systems subject to communication constraints, in which nonlinear subsystems interconnected via dynamics and by constraints. The interconnections are relaxed by using gradient method, accelerated gradient and alternating direction methods of multipliers. Also, an event-based communication is proposed to handle the issue of communication constraints especially in embedded systems. In the proposed event-based communication strategy, each controller solves the optimization problem and communicate only if the prices are updated significantly, which can reduce the computation load and release the burden of the network while achieving global performance. Finally, the simulations study of the four-tank benchmark is presented to demonstrate the effectiveness of the proposed schemes.

Nonlinear distributed model predictive control for complex systems: application for hydraulic system

2018 ◽  
Vol 41 (10) ◽  
pp. 2751-2763 ◽  
Author(s):  
Nadia Hajji ◽  
Saber Maraoui ◽  
Larbi Chrifi-Alaoui ◽  
Kais Bouzrara
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Hydraulic System ◽  
Water Levels ◽  
Distributed Model ◽  
Dual Decomposition ◽  
Decomposition Approach ◽  
Distributed Model Predictive Control ◽  
Nonlinear Predictive Control ◽  
Tank System

In this paper, a nonlinear distributed model predictive control based on dual decomposition approach is proposed for complex system. The global system can be decomposed into several subsystems and each one will be managed by its own controller. To design the nonlinear predictive control in a distributed fashion, an analytical solution is proposed. The latter is based on the approximation of the error using its expansion of Taylor series. The proposed approach is implemented on the three tank system to control the water levels. Simulation results demonstrate the effectiveness of the proposed approach.

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