Research on Air Conditioning System of Subway Station Based on Fuzzy PID Control

2017 ◽  
Author(s):  
Lian Li ◽  
Dong Jia
Keyword(s):  
Pid Control ◽  
Air Conditioning ◽  
Subway Station ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Air Conditioning System

Intelligent Information Control for Air System

2013 ◽  
Vol 310 ◽  
pp. 502-505
Author(s):  
Jun Zhou
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Air Conditioning ◽  
Information Control ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Air Conditioning System ◽  
Adaptive Fuzzy ◽  
Technical Requirements ◽  
Adaptive Fuzzy Pid Control

PID control has been widely applied in the industrial process control because of its robust and easy realization, but it is difficult to tune the parameters of PID controller, which often leads to oscillation and overshoot. Due to no repetition and random of adaptive fuzzy PID control, the authors propose a method to search for normalization PID controller parameters based on adaptive fuzzy PID control, which can be expected to have higher ability of searching for global optimal PID parameters according to the performance index of control system . The MATLAB simulation of the Adaptive fuzzy PID controller and a PID controller were carried out on the Air Conditioning System temperature. Results showed that: Response time of Adaptive fuzzy PID was 0.46 s., and maximum overshoot didn’t exceed 3.29%.The stability accuracy and rapidity of the system were able to satisfy the Air Conditioning System technical requirements.

Adaptive PID Control for the Air-Conditioning System in Spray-Paint Workshop Based on Fuzzy Logic

2012 ◽  
Vol 433-440 ◽  
pp. 5733-5738
Author(s):  
Jie Dong
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Air Conditioning ◽  
Good Control ◽  
Heating System ◽  
Fuzzy Pid ◽  
Air Conditioning System ◽  
Fuzzy Pid Controller ◽  
Robust Property ◽  
Adaptive Pid Control

As the improvement of the modern workshop’s demand for cool supply, heating system, how to effectively manage the air-conditioning equipments to satisfy the production skills for air-conditioning system has become an important subject for modern workshop design. This paper comes from the No.1 motorcar company’s project about the automatic air-conditioning system of the car spray-paint workshop. For many reasons, the conventional PID control is difficult to satisfy the car spray-paint production’s strictly demands of the temperature, after a careful research of the object, we utilize the principle of fuzzy PID adaptive control to design a fuzzy PID controller, then put it into the air-conditioning heater’s controlling, through the practice, we find the controller has a good robust property and realized a good control result.

Application of Fuzzy PID for the Ventilation and Air Conditioning System of Subway Station

2011 ◽  
Vol 128-129 ◽  
pp. 811-814
Author(s):  
Jia Wang ◽  
Feng Wang ◽  
Yong Jiang ◽  
Zhi Xin Chen ◽  
Shi Tian Yan
Keyword(s):  
Air Conditioning ◽  
Parameter Tuning ◽  
Subway Station ◽  
Fuzzy Pid ◽  
Control Effect ◽  
Air Conditioning System ◽  
Fuzzy Pid Controller ◽  
Quality Of Control ◽  
On Line ◽  
Excellent Control

The ventilation and air conditioning system in the public area of subway station is a complex system which possesses a problem by once setting parameters of PID is difficult to ensure excellent control effect. Therefore this paper proposed an algorithm to adopt parameter tuning that could adjust the PID parameters on real time to ensure good quality of control system. It combined fuzzy logic control with conventional PID control algorithm, with the help of fuzzy tuning of PID parameters on line to change the control effect. By simulation, fuzzy PID controller could get better in control effect, higher in control accuracy, stronger in robustness than before.

Application of Fuzzy PID for the Ventilation and Air Conditioning System of Subway Station

2012 ◽  
Vol 6 (1) ◽  
pp. 821-823
Author(s):  
Wang Jia ◽  
Wang Feng ◽  
Jiang Yong ◽  
Chen Zhixin ◽  
Yan Shitian
Keyword(s):  
Air Conditioning ◽  
Subway Station ◽  
Fuzzy Pid ◽  
Air Conditioning System

Simulation of Indoor Temperature Control in VAV Air Conditioning System Based on Fuzzy PID and Smith Predictor Controller

2014 ◽  
Vol 556-562 ◽  
pp. 2401-2405 ◽  
Author(s):  
Tian Tian Guo ◽  
Qi Gao Hu
Keyword(s):  
Temperature Control ◽  
Air Conditioning ◽  
Control Algorithm ◽  
Current Control ◽  
Smith Predictor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Indoor Temperature ◽  
Air Conditioning System ◽  
Indoor Temperature Control

A Fuzzy PID-Smith Control algorithm is proposed based on Fuzzy PID Control and Smith Predictor Control for the indoor temperature control of VAV air conditioning system which is a big inertia, pure time-delay, nonlinearity and greatly affected by circumstances complex temperature system. The algorithm flow and fuzzy reasoning rules were designed and it possesses the advantages of both Fuzzy PID and Smith Predictor. The simulation results show that the algorithm has fast response, small overshoot, high accuracy, strong robust and self-setting in line when the parameter changes and a great improvement in the aspects of overshoot and adjusting time has been achieved compared to the current control algorithm.

scholarly journals Air Conditioning Energy Saving from Cloud-Based Artificial Intelligence: Case Study of a Split-Type Air Conditioner

Energies ◽  
2020 ◽  
Vol 13 (8) ◽  
pp. 2001 ◽  
Author(s):  
Dasheng Lee ◽  
Fu-Po Tsai
Keyword(s):  
Artificial Intelligence ◽  
Energy Efficiency ◽  
Energy Saving ◽  
Pid Control ◽  
Air Conditioning ◽  
Efficiency Index ◽  
Air Conditioner ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Air Conditioners

This study developed cloud-based artificial intelligence (AI) that could run AI programs in the cloud and control air conditioners remotely from home. AI programs in the cloud can be altered any time to provide good control performances without altering the control hardware. The air conditioner costs and prices can thus be reduced by the increasing energy efficiency. Cloud control increased energy efficiency through AI control based on two conditions: (1) a constant indoor cooling rate and (2) a fixed stable range of indoor temperature control. However, if the two conditions cannot be guaranteed or the cloud signals are lost, the original proportional-integral-differential (PID) control equipped in the air conditioner can be used to ensure that the air conditioner works stably. The split-type air conditioner tested in this study is ranked eighth among 1177 air conditioners sold in Taiwan according to public data. It has extremely high energy efficiency, and using AI to increase its energy efficiency was challenging. Thus, this study analyzed the literature of AI-assisted controls since 1995 and applied it to heating, ventilation, and air conditioning equipment. Two technologies with the highest energy saving efficiency, a fuzzy + PID and model-based predictive control (MPC), were chosen to be developed into two control methodologies of cloud-based AI. They were tested for whether they could improve air conditioning energy efficiency. Energy efficiency measurement involved an enthalpy differential test chamber. The two indices, namely the energy efficiency ratio (EER) and cooling season power factor (CSPF), were tested. The EER measurement is the total efficiency value obtained when testing the required electric power at the maximum cooling capacity under constantly controlled temperature and humidity. CSPF is the tested efficiency value under dynamic conditions from changing indoor and outdoor temperatures and humidity according to the climate conditions in Taiwan. By using the static energy efficiency index EER for evaluation, the fuzzy + PID control could not save energy, but MPC increased the EER value by 9.12%. By using the dynamic energy efficiency index CSPF for evaluation, the fuzzy + PID control could increase CSPF by 3.46%, and MPC could increase energy efficiency by 7.37%.

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