**:** ..,

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**:** 2018
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** :**
**:** 75
**:** .., .., .. // . 75. .: , 2018. .146-169. URL: https://doi.org/10.25728/ubs.2018.75.7

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** :** , , Model Predictive Control, , MATLAB

** (.):** indoor environment, energy and resource efficiency, Model Predictive Control, hierarchical optimal control, MATLAB

**:** . (MPC-). . MPC- . , . , , . . MPC- , MPC- . , , , , , , .

** (.):** In this article, the problem of energy-efficient control of the indoor environment of large multi-zone buildings is considered. To solve this problem, it is proposed to use the hierarchical, distributed, predictive optimal control method (MPC approach). This method allows you to achieve a minimum of the global quality criterion and the implementation of restrictions for the whole system, taking into account the interrelationships between subsystems. When implementing a hierarchical distributed MPC-algorithm, there arises the problem of coordinated solution for the mathematical programming problems for each of the subsystems. To solve the global problem of mathematical programming, the authors propose a method based on the decomposition method via resource sharing. The authors prove that under certain assumptions on sets of admissible solutions for local problems, if the local optimization problems have a solution, then the coordination problem will have an admissible optimal solution. Numerical results are presented in order to illustrate the effectiveness of the proposed control strategy. As a result of comparison of various variants of the optimal control implementation, it is established that hierarchical distributed approach provides the best compliance with the limitations and the greatest energy saving. The availability of various types of energy resources allows, for example, in case of a sharp increase in the household needs consumption of thermal energy during peak hours, to increase the input of electricity to maintain the required microclimate.

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