Abstract
This study proposes the flow and temperature controllers of a cockpit environment control system (ECS) by implementing an optimal simplified swarm optimization (SSO) fuzzy proportional-integral-derivative (PID) control. The ECS model is considered as a multiple-input multiple-output (MIMO) and second-order dynamic system, which is interactive. In this work, we use five methods to design and compare the PID controllers in MATLAB and Simulink, including Ziegler–Nicolas PID tuning, particle swarm optimization (PSO) PID, SSO PID, and the combination of the fuzzy theory with PSO PID and SSO PID, respectively. The main contribution of this study is the pioneering implementation of SSO in a fuzzy PI/PID controller. Moreover, by adding the original gain parameters Kp, Ki, and Kd in the PID controller with delta values, which are calculated by fuzzy logic designer, we can tune the parameters of PID controllers in real time. This makes our control system more accurate, adaptive, and robust.
Highlights
It is important for an aircraft pilot to fly at a comfortable temperature and for the avionics in the cockpit to dissipate heat and operate smoothly
The following figures depict the responses of flow and temperature after receiving the unit step function input in Simulink using Ziegler–Nichols test (Z–N) PID (Figures 16 and 17), particle swarm optimization (PSO) PID and simplified swarm optimization (SSO) PID
The following figures depict the responses of flow and temperature after receiving the unit step function input in Simulink using Z–N PID (Figures 16 and 17), PSO PID and SSO PID (Figures 18 function input in Simulink using Z–N PID (Figures 16 and 17), PSO PID and SSO PID (Figures 18 and and 19), PSO fuzzy PID and SSO fuzzy PID (Figures 20 and 21), and SSO fuzzy PI (Figures 22 and 23)
Summary
It is important for an aircraft pilot to fly at a comfortable temperature and for the avionics in the cockpit to dissipate heat and operate smoothly. In the cockpit environment control system (ECS), the temperature and air flow control are important technologies and issues. The system for temperature and air flow control is called the environmental control system. The most critical technological issue for generating an appropriate air flow rate and temperature is to control the cold and hot air flows and mix them to reach the desired value. It is a complex multiple-input multiple-output (MIMO) problem [1]
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