The Experts below are selected from a list of 13581 Experts worldwide ranked by ideXlab platform
Jun Mei - One of the best experts on this subject based on the ideXlab platform.
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an autonomous hierarchical control for improving indoor comfort and energy efficiency of a direct expansion air conditioning system
Applied Energy, 2018Co-Authors: Jun Mei, Xiaohua Xia, Mengjie SongAbstract:Abstract This paper presents an autonomous hierarchical control method for a direct expansion air conditioning system. The control objective is to maintain both thermal comfort and indoor air quality at required levels while reducing energy consumption and cost. This control method consists of two layers. The upper layer is an Open Loop Controller that allows obtaining tradeoff steady states by optimizing the energy cost of the direct expansion air conditioning system and the value of predicted mean vote under the time-of-use price structure of electricity. On the other hand, the lower layer designs a model predictive Controller, which is in charge of tracking the tradeoff steady states calculated by the upper layer. Control performance of the proposed control method is compared to a conventional control strategy. The results show that the proposed control strategy reduces the energy consumption and energy cost of the direct expansion air conditioning system by 31.38% and 33.85%, respectively, while maintaining both the thermal comfort and indoor air quality within acceptable ranges, which validate the proposed methodology in terms of both comfort and energy efficiency.
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energy efficient predictive control of indoor thermal comfort and air quality in a direct expansion air conditioning system
Applied Energy, 2017Co-Authors: Jun Mei, Xiaohua XiaAbstract:Generally, conventional Controllers for comfort are designed by using on/off control or proportional-integral (PI) control, with little consideration of energy consumption of the system. This paper presents a multi-input-multi-output (MIMO) model predictive control (MPC) for a direct expansion (DX) air conditioning (A/C) system to improve both indoor thermal comfort and air quality, whereas the energy consumption is minimised. The DX A/C system is modelled into a nonlinear system, with a varying speed of compressor and varying speed of supply fan and volume flow rate of supply air being regarded as inputs. We first propose an Open Loop Controller based on an optimisation of energy consumption with the advantage of a unique set of steady states. The MPC Controller is proposed to optimise the transient processes reaching the steady state. To facilitate the MPC design, the nonlinear model is linearised around its steady state. MPC is designed for the linearised model. The advantages of the proposed energy-optimised Open Loop Controller and the closed-Loop regulation of the MIMO MPC scheme are verified by simulation results.
Xiaohua Xia - One of the best experts on this subject based on the ideXlab platform.
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an autonomous hierarchical control for improving indoor comfort and energy efficiency of a direct expansion air conditioning system
Applied Energy, 2018Co-Authors: Jun Mei, Xiaohua Xia, Mengjie SongAbstract:Abstract This paper presents an autonomous hierarchical control method for a direct expansion air conditioning system. The control objective is to maintain both thermal comfort and indoor air quality at required levels while reducing energy consumption and cost. This control method consists of two layers. The upper layer is an Open Loop Controller that allows obtaining tradeoff steady states by optimizing the energy cost of the direct expansion air conditioning system and the value of predicted mean vote under the time-of-use price structure of electricity. On the other hand, the lower layer designs a model predictive Controller, which is in charge of tracking the tradeoff steady states calculated by the upper layer. Control performance of the proposed control method is compared to a conventional control strategy. The results show that the proposed control strategy reduces the energy consumption and energy cost of the direct expansion air conditioning system by 31.38% and 33.85%, respectively, while maintaining both the thermal comfort and indoor air quality within acceptable ranges, which validate the proposed methodology in terms of both comfort and energy efficiency.
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energy efficient predictive control of indoor thermal comfort and air quality in a direct expansion air conditioning system
Applied Energy, 2017Co-Authors: Jun Mei, Xiaohua XiaAbstract:Generally, conventional Controllers for comfort are designed by using on/off control or proportional-integral (PI) control, with little consideration of energy consumption of the system. This paper presents a multi-input-multi-output (MIMO) model predictive control (MPC) for a direct expansion (DX) air conditioning (A/C) system to improve both indoor thermal comfort and air quality, whereas the energy consumption is minimised. The DX A/C system is modelled into a nonlinear system, with a varying speed of compressor and varying speed of supply fan and volume flow rate of supply air being regarded as inputs. We first propose an Open Loop Controller based on an optimisation of energy consumption with the advantage of a unique set of steady states. The MPC Controller is proposed to optimise the transient processes reaching the steady state. To facilitate the MPC design, the nonlinear model is linearised around its steady state. MPC is designed for the linearised model. The advantages of the proposed energy-optimised Open Loop Controller and the closed-Loop regulation of the MIMO MPC scheme are verified by simulation results.
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Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs
Energy, 2015Co-Authors: Nnamdi Nwulu, Xiaohua XiaAbstract:Abstract In this paper, a game theory demand response program is incorporated into two problems; the dynamic economic emission dispatch problem and the price based dynamic economic emission dispatch problem. The game theory demand response program is an incentive based program which provides monetary incentives for willing customers who agree to curtail their demand, with the incentive greater than or equals to the their cost of curtailment. Both mathematical problems are multi-objective optimization problems and for the first model, the objectives are to minimize fuel costs and emissions and determine the optimal incentive and load curtailment for customers. The second model seeks to minimize emissions, maximize profits and also determine the optimal incentive and load curtailment for customers. Model predictive control, which is known as a closed Loop approach from a control perspective is deployed to solve both proposed mathematical models and a comparison is provided with solutions obtained via an Open Loop approach. Obtained results validate the superiority of the closed Loop approach over the Open Loop Controller. For instance the closed Loop approach yields 4.36 MWh and 11.35 MWh higher customer energy curtailments than the Open Loop approach for the first and second models respectively. Furthermore, obtained results also prove that the closed Loop control approach shows better robustness against uncertainties and disturbance.
Mengjie Song - One of the best experts on this subject based on the ideXlab platform.
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an autonomous hierarchical control for improving indoor comfort and energy efficiency of a direct expansion air conditioning system
Applied Energy, 2018Co-Authors: Jun Mei, Xiaohua Xia, Mengjie SongAbstract:Abstract This paper presents an autonomous hierarchical control method for a direct expansion air conditioning system. The control objective is to maintain both thermal comfort and indoor air quality at required levels while reducing energy consumption and cost. This control method consists of two layers. The upper layer is an Open Loop Controller that allows obtaining tradeoff steady states by optimizing the energy cost of the direct expansion air conditioning system and the value of predicted mean vote under the time-of-use price structure of electricity. On the other hand, the lower layer designs a model predictive Controller, which is in charge of tracking the tradeoff steady states calculated by the upper layer. Control performance of the proposed control method is compared to a conventional control strategy. The results show that the proposed control strategy reduces the energy consumption and energy cost of the direct expansion air conditioning system by 31.38% and 33.85%, respectively, while maintaining both the thermal comfort and indoor air quality within acceptable ranges, which validate the proposed methodology in terms of both comfort and energy efficiency.
Simon M Lucas - One of the best experts on this subject based on the ideXlab platform.
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evolving Controllers for simulated car racing
arXiv: Neural and Evolutionary Computing, 2006Co-Authors: Julian Togelius, Simon M LucasAbstract:This paper describes the evolution of Controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track. Five different Controller architectures were compared, based on neural networks, force fields and action sequences. The Controllers use either egocentric (first person), Newtonian (third person) or no information about the state of the car (Open-Loop Controller). The only Controller that was able to evolve good racing behaviour was based on a neural network acting on egocentric inputs.
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evolving Controllers for simulated car racing
Congress on Evolutionary Computation, 2005Co-Authors: Julian Togelius, Simon M LucasAbstract:This paper describes the evolution of Controllers for racing a simulated radio-controlled car around a track, modelled on a real physical track. Five different Controller architectures were compared, based on neural networks, force fields and action sequences. The Controllers use egocentric (first person), Newtonian (third person) or no information about the state of the car (Open-Loop Controller). The only Controller that able to evolve good racing behaviour was based on neural network acting on egocentric inputs.
Alexandre M Bayen - One of the best experts on this subject based on the ideXlab platform.
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feed forward control of Open channel flow using differential flatness
IEEE Transactions on Control Systems and Technology, 2010Co-Authors: Tarek Rabbani, F Di Meglio, X Litrico, Alexandre M BayenAbstract:This brief derives a method for Open-Loop control of Open channel flow, based on the Hayami model, a parabolic partial differential equation resulting from a simplification of the Saint-Venant equations. The Open-Loop control is represented as infinite series using differential flatness, for which convergence is assessed. A comparison is made with a similar problem available in the literature for thermal systems. Numerical simulations show the effectiveness of the approach by applying the Open-Loop Controller to irrigation canals modeled by the full Saint-Venant equations.
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flatness based control of Open channel flow in an irrigation canal using scada applications of control
IEEE Control Systems Magazine, 2009Co-Authors: T Rabbani, Alexandre M Bayen, Simon Munier, David Dorchies, Pierreolivier Malaterre, X LitricoAbstract:This article applied a flatness-based Controller to an Open channel hydraulic canal. The Controller was tested by computer simulation using Saint-Venant equations as well as by real experimentation on the Gignac canal in southern France. The initial model that assumes constant lateral withdrawals is improved to take into account gravitational lateral withdrawals, which vary with the water level. Accounting for gravitational lateral withdrawals decreased the steady-state error from 6.2% (constant lateral withdrawals assumption) to 1% (gravitational lateral withdrawals assumption). The flatness-based Open-Loop Controller is thus able to compute the upstream water discharge corresponding to a desired downstream water discharge, taking into account the gravitational withdrawals along the canal reach.
