[go: up one dir, main page]

Sha et al., 2023 - Google Patents

A control strategy of heating system based on adaptive model predictive control

Sha et al., 2023

Document ID
15924713259075246649
Author
Sha L
Jiang Z
Sun H
Publication year
Publication venue
Energy

External Links

Snippet

Abstract Space heating accounts for a large proportion of a building's energy consumption, and improving heating efficiency is a significant approach to reduce heating energy consumption and carbon emissions. To improve heating efficiency and meet the demand for …
Continue reading at www.sciencedirect.com (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
    • 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
    • G05B13/0275—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 fuzzy logic 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
    • G05B13/0205—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
    • 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
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control 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
    • G05B2219/30—Nc systems
    • 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
    • G05B21/00—Systems involving sampling of the variable controlled

Similar Documents

Publication Publication Date Title
Sha et al. A control strategy of heating system based on adaptive model predictive control
Olu-Ajayi et al. Building energy consumption prediction for residential buildings using deep learning and other machine learning techniques
Lee et al. Model predictive control of building energy systems with thermal energy storage in response to occupancy variations and time-variant electricity prices
Mustafaraj et al. Development of room temperature and relative humidity linear parametric models for an open office using BMS data
Mustafaraj et al. Prediction of room temperature and relative humidity by autoregressive linear and nonlinear neural network models for an open office
Huang et al. A new model predictive control scheme for energy and cost savings in commercial buildings: An airport terminal building case study
Kusiak et al. Minimization of energy consumption in HVAC systems with data-driven models and an interior-point method
Zhang et al. A deep reinforcement learning approach to using whole building energy model for hvac optimal control
Široký et al. Experimental analysis of model predictive control for an energy efficient building heating system
Afram et al. Artificial neural network (ANN) based model predictive control (MPC) and optimization of HVAC systems: A state of the art review and case study of a residential HVAC system
Ben-Nakhi et al. Energy conservation in buildings through efficient A/C control using neural networks
Gao et al. Energy saving and indoor temperature control for an office building using tube-based robust model predictive control
Perera et al. Control of temperature and energy consumption in buildings-a review.
Qin et al. Energy-efficient heating control for nearly zero energy residential buildings with deep reinforcement learning
Lee et al. Simplified data-driven models for model predictive control of residential buildings
Jang et al. Prediction of optimum heating timing based on artificial neural network by utilizing BEMS data
Hou et al. Nonlinear model predictive control for the space heating system of a university building in Norway
Zhao et al. Real-time energy consumption prediction method for air-conditioning system based on long short-term memory neural network
Hilliard et al. Development of a whole building model predictive control strategy for a LEED silver community college
Khanmirza et al. Design and experimental evaluation of model predictive control vs. intelligent methods for domestic heating systems
Ma et al. Model predictive control of building energy systems with balanced model reduction
Erfani et al. Design and construction of a non-linear model predictive controller for building's cooling system
Chen et al. Sensitivity analysis of physical regularization in physics-informed neural networks (PINNs) of building thermal modeling
Zhang et al. A new model predictive control approach integrating physical and data-driven modelling for improved energy performance of district heating substations
Urrutia et al. Model predictive control with self-learning capability for automated demand response in buildings