Automatic Aircraft Cabin Pressurization Systems

2019 ◽  
pp. 20-25
Author(s):  
Z.S. Sukhov ◽  
G.A. Timofeev
Keyword(s):  
Control Systems ◽  
Pid Controller ◽  
Pressure Control ◽  
Adaptive Controller ◽  
Testing Environment ◽  
Fuzzy Pid Controller ◽  
New Methods ◽  
Automatic Pressure ◽  
L1 Adaptive Controller ◽  
The Cost

This article presents a review of pneumatic, electro-pneumatic and digital systems for automatic pressure control in an airtight cabin and lists the types of aircraft where such systems are installed. Advanced algorithms for controlling the pressure in an airtight cabin are analyzed and literature on this topic is surveyed. The work of a Russian author that describes optimal control based on Pontryagin’s maximum principle is examined. The works of foreign authors on fuzzy PID-controller, L1-adaptive controller and other methods of adaptive pressurization are analyzed and brief results of these works are presented. The performed analysis indicates the need to use new methods and approaches to the synthesis of automatic pressure control systems for various types of aircraft. One of the most promising solutions is the use of adaptive regulators. The relevance of developing a virtual testing environment to reduce the cost of full-scale testing is shown.

L1 Adaptive Control for Aircraft Air Management System Pressure-Regulating Bleed Valve

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
John Cooper ◽  
Chengyu Cao ◽  
Jiong Tang
Keyword(s):  
Management System ◽  
Control Valve ◽  
Pressure Control ◽  
Adaptive Controller ◽  
System Model ◽  
Flow Control Valve ◽  
L1 Adaptive Control ◽  
System Pressure ◽  
L1 Adaptive Controller ◽  
Linear Controllers

This paper presents an L1 adaptive controller for pressure control using an engine bleed valve in an aircraft air management system (AMS). The air management system is composed of two pressure-regulating bleed valves, a temperature control valve, a flow control valve, and a heat exchanger/precooler. Valve hysteresis due to backlash and dry friction is included in the system model. The nonlinearities involved in the system cause oscillations under linear controllers, which decrease component life. This paper is the unique in the consideration of these uncertainties for control design. This paper presents simulation results using the adaptive controller and compares them to those using a proportional–integral (PI) controller.

scholarly journals PID and Fuzzy-PID Control Model for Quadcopter Attitude with Disturbance Parameter

2017 ◽  
Vol 12 (4) ◽  
pp. 519 ◽  
Author(s):  
Endrowednes Kuantama ◽  
Tiberiu Vesselenyi ◽  
Simona Dzitac ◽  
Radu Tarca
Keyword(s):  
Control System ◽  
Control Systems ◽  
Pid Controller ◽  
Vital Role ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Circular Trajectory ◽  
Attitude Stability ◽  
Fuzzy Pid Controller ◽  
Error Magnitude

This paper aims to present data analysis of quadcopter dynamic attitude on a circular trajectory, specifically by comparing the modeling results of conventional Proportional Integral Derivative (PID) and Fuzzy-PID controllers. Simulations of attitude stability with both control systems were done using Simulink toolbox from Matlab so the identification of each control system is clearly seen. Each control system algorithm related to roll and pitch angles which affects the horizontal movement on a circular trajectory is explained in detail. The outcome of each tuning variable of both control systems on the output movement is observable while the error magnitude can be compared with the reference angles. To obtain a deeper analysis, wind disturbance on each axis was added to the model, thus differences between each control system are more recognizable. According to simulation results, the Fuzzy-PID controller has relatively smaller errors than the PID controller and has a better capability to reject disturbances. The scaling factors of gain values of the two controllers also play a vital role in their design.

Guiding mechanism design and precision pressure control in composites filament winding system

2016 ◽  
Vol 231 (4) ◽  
pp. 616-634
Author(s):  
Pengbing Zhao ◽  
Jinzhu Zhou ◽  
Jin Huang
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Pressure Control ◽  
Experimental Results ◽  
Nonlinear Flow ◽  
Grey Prediction ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Pressure Control System ◽  
Rolling Guide

During the composite winding process, pressure fluctuation will affect the density and homogeneity of the products and will make the interfacial strength disaccord with the fiber volume fraction. In order to improve the guiding precision and stability of the winding pressure, the bearing guide is replaced by the rolling guide in designing the pressure guiding mechanism, and parametric model of the guiding mechanism is established based on dynamics experiment of the joint surfaces. By analyzing the modal and harmonic response, the corresponding measures for improvement are proposed. Experimental results show that the designed guiding mechanism based on the rolling guide has high precision and perfect stability. Additionally, roundness error and installation error of the mandrel can cause the winding pressure to fluctuate and the gas compressibility, nonlinear flow, dead zone, cylinder friction, measurement noise and other nonlinear disturbances have significant impact on the pneumatic pressure control system. Considering the above circumstance, an adaptive fuzzy proportional–integral–derivative (PID) controller based on the grey prediction is proposed. By predicting the output pressure, trend of the pressure signal can be reflected accurately, which provides a reliable basis for the decision-making of the fuzzy PID controller. Simultaneously, two separate fuzzy inference systems are employed to adjust the step length of the predictive control and the scale factor of the step self-tuning algorithm. Simulation and experimental results show that the fuzzy PID controller based on grey prediction has shorter settling time, smaller overshoot and error, stronger robustness and interference immunity. The designed guiding mechanism and control algorithm have effectively improved the precision and stability of the pressure control system for the composite materials winding formation.

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