Keywords:Energy-efficient buildings, Simscape TM models, Model Predictive Control, Multi-room building model. Abstract:This paper deals with the problem of modelling and controlling a multi-zone office building to ensure its thermal comfort by an optimal and cost effective management of the energy consumption. A thermal behaviour analysis of the building is carried out using the Simscape TM library in MATLAB/Simulink R environment that leads to a multi-model representation. Based on this modelling, the Yalmip toolbox in the MATLAB programming environment or an iterative optimization algorithm can be used to solve the control optimisation problem. The design of a model predictive control associated with a wise choice of the cost function makes it possible to obtain in simulation substantial energy benefits.

This article deals with the problem of modeling a multi-zone office building to ensure its hygrothermal comfort. An analysis of the hygrothermal behavior is carried out using a nodal method based on the SimscapeTM library in MATLAB/Simulink R environment. The application target is the "Eco-Safe" platform (CRAN Nancy, France) that fits in a global context of smart home [1].

This paper presents a new methodology for distributed model predictive control of large-scale systems. The methodology involves two distinct stages, i.e., the decomposition of large-scale systems into subsystems and the design of subsystem controllers. Two procedures are used: in the first stage, the structure of the Karush-Kuhn-Tucker matrix resulting from the necessary optimality conditions is exploited to yield a decomposition of the large-scale system into several subsystems. In the second stage, a particular technique, the socalled optimality condition decomposition makes it possible to synthesize distributed coordinated subcontrollers thus achieving an optimal distributed control of the large-scale system. The convergence of the proposed approach is stated.

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