JP-7856232-B2 - Air conditioning control device and program therefor

JP7856232B2JP 7856232 B2JP7856232 B2JP 7856232B2JP-7856232-B2

Inventors

村松哲
深津卓弥
菱沼徹

Assignees

トリニティ工業株式会社
株式会社Proxima Technology

Dates

Publication Date: 20260511
Application Date: 20220317

Claims (9)

An air conditioning control device for controlling the amount of operation of air conditioning equipment in an air conditioning system that adjusts the temperature and humidity of incoming outside air using multiple types of air conditioning equipment, A first air conditioning control unit controls the amount of operation of the air conditioning equipment by PID control, A second air conditioning control unit controls the amount of operation of the air conditioning equipment by model predictive control based on a predictive model, A calculation and comparison unit calculates and compares the energy required to bring the conditioned air to the target point using the PID control and the energy required to bring the conditioned air to the target point using the model predictive control. A control switching unit that automatically switches to the air conditioning control unit that requires less energy to get the conditioned air to the target point, among the first air conditioning control unit and the second air conditioning control unit , The learning data collection unit collects learning data for the prediction model by performing random excitation of the air conditioning equipment, which is an operation that returns the air conditioning air condition point that has been displaced from a learning start point set within the prediction model creation area on the psychrometric chart to the learning start point using the PID control, at multiple learning start points set at different locations within the prediction model creation area. An air conditioning control device characterized by being equipped with
An air conditioning control device for controlling the amount of operation of air conditioning equipment in an air conditioning system that adjusts the temperature and humidity of incoming outside air using multiple types of air conditioning equipment, A first air conditioning control unit controls the amount of operation of the air conditioning equipment using PID control, A second air conditioning control unit controls the amount of operation of the air conditioning equipment by model predictive control based on a predictive model, A calculation and comparison unit calculates and compares the deviation from the target value when the conditioned air reaches the target point using the PID control and the deviation from the target value when the conditioned air reaches the target point using the model predictive control. A control switching unit that automatically switches to the air conditioning control unit that has a smaller deviation from the target value when the conditioned air reaches the target point, among the first air conditioning control unit and the second air conditioning control unit, and performs control accordingly . The learning data collection unit collects learning data for the prediction model by performing random excitation of the air conditioning equipment, which is an operation that returns the air conditioning air condition point that has been displaced from a learning start point set within the prediction model creation area on the psychrometric chart to the learning start point using the PID control, at multiple learning start points set at different locations within the prediction model creation area. An air conditioning control device characterized by being equipped with
The air conditioning control device according to claim 1 or 2, characterized in that the learning data collection unit collects learning data for additional training of the prediction model while the first air conditioning control unit is performing the PID control.
The air conditioning control device according to claim 3, further comprising a machine learning unit that creates a new prediction model based on the learning data collected by the learning data collection unit while the first air conditioning control unit is performing the PID control.
The air conditioning control device according to claim 1 or 2, further comprising a sequential learning unit that continuously improves the error of the prediction model by sequentially providing the control results as learning data for each control step while the second air conditioning control unit is performing the model predictive control.
The air conditioning control device according to claim 4 or 5, characterized in that, upon completion of the new prediction model, the control switching unit updates the old prediction model by replacing it with the latest prediction model, and then switches from the first air conditioning control unit to the second air conditioning control unit to perform control.
The air conditioning control device according to any one of claims 1 to 6, characterized in that the air conditioning system is an air conditioning system for painting equipment, and the air conditioning equipment is an air conditioner for a painting booth including a preheating device, a humidifying device, a cooling device, and a reheating device.
A program for operating an air conditioning control device comprising an air conditioning system that adjusts the temperature and humidity of incoming outside air using multiple types of air conditioning equipment, a first air conditioning control unit that controls the operation amount of the air conditioning equipment by PID control, and a second air conditioning control unit that controls the operation amount of the air conditioning equipment by model predictive control based on a predictive model, A calculation and comparison step involves calculating and comparing the energy required to bring the conditioned air to the target point using the PID control and the energy required to bring the conditioned air to the target point using the model predictive control. A control switching step that automatically switches to the air conditioning control unit that requires less energy to get the conditioned air to the target point, among the first air conditioning control unit and the second air conditioning control unit, and performs control ; The learning data collection operation, which involves collecting learning data for the prediction model by performing random excitation of the air conditioning equipment, which is the operation of returning the air conditioning air condition point that has been displaced from a learning start point set within the prediction model creation area on the psychrometric chart to the learning start point using the PID control, at multiple learning start points set at different locations within the prediction model creation area, is performed while the first air conditioning control unit is performing the PID control; A program for an air conditioning control device, characterized by including the following:
A program for operating an air conditioning control device comprising an air conditioning system that adjusts the temperature and humidity of incoming outside air using multiple types of air conditioning equipment, a first air conditioning control unit that controls the operation amount of the air conditioning equipment by PID control, and a second air conditioning control unit that controls the operation amount of the air conditioning equipment by model predictive control based on a predictive model, A calculation and comparison step involves calculating and comparing the deviation from the target value when the conditioned air reaches the target point using the PID control and the deviation from the target value when the conditioned air reaches the target point using the model predictive control. A control switching step that automatically switches to the air conditioning control unit that has a smaller deviation from the target value when the conditioned air reaches the target point, among the first air conditioning control unit and the second air conditioning control unit , and performs control; The learning data collection operation, which involves collecting learning data for the prediction model by performing random excitation of the air conditioning equipment, which is the operation of returning the air conditioning air condition point that has been displaced from a learning start point set within the prediction model creation area on the psychrometric chart to the learning start point using the PID control, at multiple learning start points set at different locations within the prediction model creation area, is performed while the first air conditioning control unit is performing the PID control; A program for an air conditioning control device, characterized by including the following:

Description

This invention relates to an air conditioning control device and a program for controlling the temperature and humidity of incoming outside air by operating multiple types of air conditioning equipment. Generally, painting facilities include equipment such as paint booths for applying paint to objects such as automobile bodies, and drying ovens for drying the paint on objects that have passed through the paint booth. In such painting facilities, air with adjusted temperature and humidity is supplied to the paint booth by a paint booth air conditioner, and painting is performed. The paint booth air conditioner consists of components such as a heating device, cooling device, humidifier (washer), and blower fan. These components are operated in combination to control the conditioned air to achieve the target temperature and humidity (see, for example, Patent Documents 1 and 2). In this case, PID control has conventionally been used for control. Incidentally, in automotive paint booths, booth air conditioners require precise temperature and humidity control to maintain the paint quality of the products. In recent years, a new method has been proposed to achieve this precise temperature and humidity control: model predictive control (MPC), which predicts future reactions while controlling the system. Model predictive control is a control method that uses a predictive model that appropriately captures and models the dynamics of the air conditioning system. Therefore, it is believed that model predictive control achieves higher control performance and makes it easier to obtain stable control results compared to conventional PID control. Patent No. 3993358Japanese Patent Publication No. 2010-119901 A block diagram illustrating an air conditioning control device according to an embodiment of the present invention.A block diagram showing in more detail the connection relationship between the air conditioning control device and the air conditioner for the paint booth in the embodiment.A flowchart illustrating the air conditioning control method performed by the air conditioning control device of the embodiment.A psychrometric chart illustrating the data acquisition method in the air conditioning control method performed by the air conditioning control device of the embodiment.A block diagram showing the connection relationship between an air conditioning control device, a paint booth air conditioner, and a heat pump in another embodiment. The air conditioning control device in an air conditioning system 11, which embodies one embodiment of the present invention, will be described in detail below with reference to Figures 1 to 4. The air conditioning system 11 of this embodiment, as shown in Figure 1, is an air conditioning system 11 for painting equipment as described above, and includes an air conditioning device 21 that adjusts the temperature and humidity of the incoming outside air using multiple types of air conditioning equipment, and an air conditioning control device 31 that controls the operating amount of the air conditioning equipment. The air conditioning device 21 in this embodiment is an air conditioner 21 for a painting booth, comprising multiple types of air conditioning equipment (preheating device, humidifying device, cooling device, reheating device, etc.). As schematically shown in Figure 1, the paint booth air conditioner 21 in the air conditioning system 11 of this embodiment includes a preheating device 22, a humidifier 23, a cooling device 24, a reheating device 25, a first sensor 27a, a second sensor 27b, a third sensor 27c, and the like. On the other hand, the air conditioning control device 31 in the air conditioning system 11 of this embodiment includes an air supply target input unit 32, an air supply setting calculation unit 33, a first air conditioning control unit 42, a second air conditioning control unit 43, a calculation comparison unit 44, a control switching unit 45, a learning data collection unit 46, a machine learning unit 47, a system identification output unit 51, and the like. Figure 2 shows a block diagram illustrating the more specific connection relationships of each element. The paint booth, to which the conditioned air generated by the paint equipment air conditioning system 11 is supplied, is generally installed in the area where paint is applied to the workpieces on the workpiece transport line. The paint booth comprises a painting chamber, an air supply chamber located above the painting chamber to supply downflow air (a constant direction from top to bottom) to the painting chamber, and an exhaust chamber located below the painting chamber to exhaust the air from the painting chamber. In this embodiment, the conditioned air discharged from the paint booth air conditioner 21 is supplied to the painting chamber from the air supply chamber via downflow. In the paint booth's painting chamber, the object to be painted is sprayed with paint mist from a painting machine (no