[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Boutchich et al., 2023 - Google Patents

A constrained model predictive control for the building thermal management with optimal setting design

Boutchich et al., 2023

View PDF
Document ID
15261126913118198928
Author
Boutchich N
Moufid A
Bennis N
Publication year
Publication venue
Int. J. Electr. Comput. Eng.(IJECE)

External Links

Snippet

Today, the building sector is the most important consumer of energy. The main challenge in building management is to obtain the desired performance taking into account many aspects such as comfort requirements, variation of building physical characteristics, system …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0205—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system
    • G05B13/024—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric not using a model or a simulator of the controlled system in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D23/00—Control of temperature
    • G05D23/19—Control of temperature characterised by the use of electric means
    • G05D23/27—Control of temperature characterised by the use of electric means with sensing element responsive to radiation
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B17/00—Systems involving the use of models or simulators of said systems
    • G05B17/02—Systems involving the use of models or simulators of said systems electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2642—Domotique, domestic, home control, automation, smart house

Similar Documents

Publication Publication Date Title
Yao et al. State of the art review on model predictive control (MPC) in Heating Ventilation and Air-conditioning (HVAC) field
Ben-Nakhi et al. Energy conservation in buildings through efficient A/C control using neural networks
Lee et al. Model predictive control of building energy systems with thermal energy storage in response to occupancy variations and time-variant electricity prices
Shaikh et al. Intelligent multi-objective optimization for building energy and comfort management
Shaikh et al. Intelligent multi-objective control and management for smart energy efficient buildings
Mustafaraj et al. Prediction of room temperature and relative humidity by autoregressive linear and nonlinear neural network models for an open office
Platt et al. Adaptive HVAC zone modeling for sustainable buildings
Thomas et al. Artificial neural network models for indoor temperature prediction: investigations in two buildings
Luzi et al. A tuning methodology of Model Predictive Control design for energy efficient building thermal control
Gruber et al. Model-based controllers for indoor climate control in office buildings–complexity and performance evaluation
Homod et al. Dynamics analysis of a novel hybrid deep clustering for unsupervised learning by reinforcement of multi-agent to energy saving in intelligent buildings
KR20170125349A (en) Method and apparatus for controlling an in-building environmental management system
Spindler et al. Naturally ventilated and mixed-mode buildings—Part I: Thermal modeling
Alamin et al. An Artificial Neural Network (ANN) model to predict the electric load profile for an HVAC system
Zhao et al. Data-driven online energy management framework for HVAC systems: An experimental study
Zhang et al. Two-stage reinforcement learning policy search for grid-interactive building control
Han et al. A review of reinforcement learning methodologies on control systems for building energy
Berouine et al. A predictive control approach for thermal energy management in buildings
Joe et al. Model-based predictive control of multi-zone commercial building with a lumped building modelling approach
Zhang et al. Diversity for transfer in learning-based control of buildings
Ding et al. Exploring deep reinforcement learning for holistic smart building control
Reynolds et al. A smart heating set point scheduler using an artificial neural network and genetic algorithm
Simon et al. Energy efficient smart home heating system using renewable energy source with fuzzy control design
Mayer et al. Cooperative and hierarchical fuzzy MPC for building heating control
Giannakis et al. A model-assisted adaptive controller fine-tuning methodology for efficient energy use in buildings