A scenario-based distributed stochastic MPC for building temperature regulation
2014 (English)In: IEEE International Conference on Automation Science and Engineering, 2014, 1091-1096 p.Conference paper (Refereed)
In this paper, we focus on the temperature regulation of rooms in buildings. By using the dynamic model of the thermal process, weather condition, occupancy and so on, a Stochastic Model Predictive Control (SMPC) problem is formulated to keep the temperature of rooms within a comfortable range with a predefined probability while consuming less energy. The temperature regulation problem in this paper is an optimal control problem of a linear system with additive uncertainty. To overcome the computational burden caused by the large number of rooms, a subgradient-based dual decomposition method is used to solve the SMPC problem in a distributed manner. Simulation results show the effectiveness of our results.
Place, publisher, year, edition, pages
2014. 1091-1096 p.
Balloons, Linear systems, Model predictive control, Optimal control systems, Predictive control systems, Problem solving, Stochastic control systems, Stochastic systems, Temperature control, Computational burden, Dual decomposition, In-buildings, Optimal control problem, Scenario-based, Subgradient, Temperature regulations, Thermal process, Stochastic models
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-175129DOI: 10.1109/CoASE.2014.6899461ScopusID: 2-s2.0-84939604777OAI: oai:DiVA.org:kth-175129DiVA: diva2:861385
2014 IEEE International Conference on Automation Science and Engineering, CASE 2014, 18 August 2014 through 22 August 2014
QC 201510162015-10-162015-10-092015-10-16Bibliographically approved