Research on Loading System of Landing Gear Turning Test Based on Single Neuron PID Controller

2014 ◽  
Vol 556-562 ◽  
pp. 2313-2316
Author(s):  
Yu Ling
Keyword(s):  
Pid Controller ◽  
Single Neuron ◽  
Fault Tolerant ◽  
Fast Response ◽  
Landing Gear ◽  
Artificial Neurons ◽  
Loading System ◽  
High Control ◽  
Single Neuron Pid ◽  
Self Learning

This paper designs a single neuron PID controller for the loading system which can simulate the load in the process of landing gear turning. As artificial neurons have the adaptive, self-learning and more fault-tolerant characteristics, the controller based on single neuron PID can improve performance of loading system. To assess the effectiveness of controller, united simulation between Matlab/Simulink and AMESim was conducted. Obtained results show the proposed approach is satisfactory in fast response, small overshoot, high control accuracy, strong anti-interference ability and robustness when compared with traditional PID controller.

Adaptive PID Controller Based on Single Neuron

2012 ◽  
Vol 466-467 ◽  
pp. 981-985 ◽  
Author(s):  
Xin Yun Qiu ◽  
Yuan Gao
Keyword(s):  
Pid Controller ◽  
Control Algorithm ◽  
Single Neuron ◽  
Variable Parameter ◽  
Fast Response ◽  
Control Law ◽  
Parameters Tuning ◽  
Application Condition ◽  
Simulation And Experiment ◽  
New Type

An adaptive PID controller based on single neuron is proposed. The properties, control algorithm, parameters tuning, the control law and the application condition of the controller are studied in the paper. To satisfy the properties of the requirements of the control system in an electromotor group, such as a broad dynamic changing range, a fast response, a little overshoot and time-variable parameter, a new-type self-optimizing PID controller based on artificial neural networks is proposed and studied. It is verified that the controller has few adjustable parameters and excellent robust performance. The results of simulation and experiment prove that the controller is superior to the traditional PID controller.

Application of Single Neuron Adaptive PID Controller in Flow Control System

2014 ◽  
Vol 602-605 ◽  
pp. 1052-1055 ◽  
Author(s):  
Ze Kang ◽  
Cheng Qiang Yin ◽  
Shao Min Teng
Keyword(s):  
Control System ◽  
Flow Control ◽  
Pid Controller ◽  
Single Neuron ◽  
Control Method ◽  
Dynamic Performance ◽  
Oxide Concentration ◽  
Flow Control System ◽  
Self Learning

Oxide concentration at reactor inlet is one of the most important factor effecting the quality of ethylene oxide concentration. A control method with adaptive PID of single neuron is propose using the parameter self-learning with adaptive PID controller of single neuron for the oxide flow control system. The simulation results show that this design scheme has a better dynamic performance than traditional PID scheme to verify the feasibility of this method.

Design and Achievement of the Erection Test System Controlled by Single Neuron PID Controller

2011 ◽  
Vol 383-390 ◽  
pp. 1983-1987
Author(s):  
Yun Ying Qiao ◽  
Xiao Song Guo ◽  
Zhi Zhu ◽  
De Lin Cun
Keyword(s):  
Virtual Instrument ◽  
Hydraulic System ◽  
Pid Controller ◽  
Single Neuron ◽  
Test System ◽  
Feedback Signal ◽  
Data Acquisition Card ◽  
Single Neuron Pid ◽  
The Stability ◽  
And Control

To overcome the nonlinear and slow-varying factor in hydraulic system and the uneasy-building model of erection system, the single neuron self-adaptive PID controller is designed. To solve the conflict between the speed and the stability in erecting, The erecting system based on virtual instrument is designed. The system uses a data acquisition card simultaneously to acquire the test data and the feedback signal and control the hydraulic system, utilizes the module method and the technique of mixed-program between LabWindows/CVI and Matlab based on ActiveX technique to design application software. The results of experiment shows that the system with high precision of testing and controlling is operated conveniently and universally and can satisfy the requirement of the erection system.

Sign in / Sign up

Export Citation Format

Share Document