Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multiv...Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multivariable decoupling PID controller is designed for VAV air-conditioning system. Diagonal matrix decoupling method is employed to eliminate the coupling between the loop of supply air temperature and that of thermal-space air temperature. The PID controller parameters are optimized by means of an improved genetic algorithm in floating point representations to obtain better performance. The population in the improved genetic algorithm mutates before crossover, which is helpful for the convergence. Additionally the micro mutation algorithm is proposed and applied to improve the convergence during the later evolution. To search the best parameters, the optimized parameters ranges should be amplified 10 times the initial ideal parameters. The simulation and experiment results show that the decoupling control system is effective and feasible. The method can overcome the strong coupling feature of the system and has shorter governing time and less over-shoot than non-optimization PID control.展开更多
Temperature and humidity are two important factors that influence both indoor thermal comfort and air quality.Through varying compressor and supply fan speeds of a direct expansion(DX)air conditioning(A/C)unit,the air...Temperature and humidity are two important factors that influence both indoor thermal comfort and air quality.Through varying compressor and supply fan speeds of a direct expansion(DX)air conditioning(A/C)unit,the air temperature and humidity in the conditioned space can be regulated simultaneously.However,most existing controllers are designed to minimize the tracking errors between the system outputs with their corresponding settings as quickly as possible.The energy consumption,which is directly influenced by the compressor and supply fan speeds,is not considered in the relevant controller formulations,and thus the system may not operate with the highest possible energy efficiency.To effectively control temperature and humidity while minimizing the system energy consumption,a model predictive control(MPC)strategy was developed for a DX A/C system,and the development results are presented in this paper.A physically-based dynamic model for the DX A/C system with both sensible and latent heat transfers being considered was established and validated by experiments.To facilitate the design of MPC,the physical model was further linearized.The MPC scheme was then developed by formulating the objective function which sought to minimize the tracking errors of temperature and moisture content while saving energy consumption.Based on the results of command following and disturbance rejection tests,the proposed MPC scheme was capable of controlling temperature and humidity with adequate control accuracy and sensitivity.In comparison to linear-quadratic-Gaussian(LQG)controller,better control accuracy and lower energy consumption could be realized when using the proposed MPC strategy to simultaneously control temperature and humidity.展开更多
基金Supported by Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education of China
文摘Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multivariable decoupling PID controller is designed for VAV air-conditioning system. Diagonal matrix decoupling method is employed to eliminate the coupling between the loop of supply air temperature and that of thermal-space air temperature. The PID controller parameters are optimized by means of an improved genetic algorithm in floating point representations to obtain better performance. The population in the improved genetic algorithm mutates before crossover, which is helpful for the convergence. Additionally the micro mutation algorithm is proposed and applied to improve the convergence during the later evolution. To search the best parameters, the optimized parameters ranges should be amplified 10 times the initial ideal parameters. The simulation and experiment results show that the decoupling control system is effective and feasible. The method can overcome the strong coupling feature of the system and has shorter governing time and less over-shoot than non-optimization PID control.
基金supports for the Science and Technology Project of Zhejiang Province(No.LGG21F030009)the Natural Science Foundation of Zhejiang Province(No.LY20F030010)the Key R&D Projects in Zhejiang Province(No.2020C01164)are gratefully acknowledged.
文摘Temperature and humidity are two important factors that influence both indoor thermal comfort and air quality.Through varying compressor and supply fan speeds of a direct expansion(DX)air conditioning(A/C)unit,the air temperature and humidity in the conditioned space can be regulated simultaneously.However,most existing controllers are designed to minimize the tracking errors between the system outputs with their corresponding settings as quickly as possible.The energy consumption,which is directly influenced by the compressor and supply fan speeds,is not considered in the relevant controller formulations,and thus the system may not operate with the highest possible energy efficiency.To effectively control temperature and humidity while minimizing the system energy consumption,a model predictive control(MPC)strategy was developed for a DX A/C system,and the development results are presented in this paper.A physically-based dynamic model for the DX A/C system with both sensible and latent heat transfers being considered was established and validated by experiments.To facilitate the design of MPC,the physical model was further linearized.The MPC scheme was then developed by formulating the objective function which sought to minimize the tracking errors of temperature and moisture content while saving energy consumption.Based on the results of command following and disturbance rejection tests,the proposed MPC scheme was capable of controlling temperature and humidity with adequate control accuracy and sensitivity.In comparison to linear-quadratic-Gaussian(LQG)controller,better control accuracy and lower energy consumption could be realized when using the proposed MPC strategy to simultaneously control temperature and humidity.
