Research Of Control System On Variable Air Volume Air-conditioner Based On The Improved Particle Swarm Algorithm

Air conditioner is the main comfort control equipment in buildings for people.However,the energy consumed by air conditioning work is also the main part of building energy consumption.In order to respond to energy conservation and emission reduction,the call for green development,reducing the energy consumption of air conditioning systems under the premise of ensuring comfort has become the subject of many scholars and experts.By adjusting the valve opening of the end device to adjust the temperature of the variable air conditioning system,the adjustment method is faster and energy saving,and has become the main research object in air conditioning systems.In this paper,the variable air volume(VAV)air conditioning system is taken as the research object.In order to obtain the mathematical model of the VAV air conditioning system,the brief composition,advantages and disadvantages of the variable air volume air conditioning system are analyzed,the sensitive factors are retained,the insensitive factors are removed,and Simulink simulation software is applied to build a mathematical model of the system.Based on this model and the law of conservation of energy,the first-order transfer function between the air supply volume and the load in the room,and the transfer functions of sensors,damper actuators,and air-conditioning end devices are obtained.Combining the bacterial foraging algorithm with good global search ability and the particle swar m algorithm with strong local search ability,the particle swarm PID is improved,so that the next direction of bacteria movement in the bacterial foraging algorithm is no longer random,which speeds up the algorithm.Convergence speed and improved algorithm accuracy.Adjusting the room temperature in this paper is achieved by changing the two factors of supply air temperature and supply air volume.In order to prevent the two controllers from interfering with each other and resonating,combining the control complexity of the variable air volume air-conditioning system and the non-linear changes in the load of the controlled room,a cascade improved particle swar m algorithm PID control loop is used to ensure the stability of the control system.In other words,the supply air temperature control is set as the main controller,and the supply air volume control is set as the sub controller.The PID parameters(k_p,k_i,k_d)of the main controller and the sub-controller are simultaneously involved in the optimization process of the bacterial foraging particle swarm algorithm,so that the cascade controllers are perfectly coordinated to achieve the optimal control effect.Compared with the improved particle swarm algorithm,the improved cascade improved particle swarm algorithm has better robustness,real-time and stability.For sudden interference in the system,this strategy can quickly meet the roo m comfort requirements More energy efficient.The PID parameters of the main controller and subcontroller are k_p?k_iand k_d participate in the optimization process of the bacterial foraging particle group algorithm at the same time,so that the string-level controllers can be well coordinated to achieve the optimal control effect.Compared with the improved particle group algorithm,the improved string-level improved particle group algorithm has better robustness,real-time and stability,and the strategy can quickly meet the room comfort requirement and be more energy-saving for the mutation interference in the system.Finally,based on the mathematical model of the variable air volume air conditioning system,an improved particle swarm optimization algorithm was used to optimize the PID control parameters,and a fitness function was designed to prevent overshoot.The simulation results were used to compare and analyze the results before and after optimization,and the effectiveness of the proposed PID control optimization method based on cascade improved particle swarm optimization algorithm was verified.