Train Speed Control Algorithm Based on PID Controller and Single-Neuron PID Controller

2010 ◽  
Author(s):  
Chen Xiangxian ◽  
Zhang Yue ◽  
Huang Hai
Keyword(s):  
Pid Controller ◽  
Control Algorithm ◽  
Single Neuron ◽  
Speed Control ◽  
Train Speed ◽  
Single Neuron Pid

Velocity Tracking Control for Hydraulic Lifting System Based on Adaptive PSD Controller

2013 ◽  
Vol 394 ◽  
pp. 398-403
Author(s):  
Chang Lin Ma ◽  
Lin Hao ◽  
Feng Li
Keyword(s):  
Tracking Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Single Neuron ◽  
Control Method ◽  
Single Neutron ◽  
Single Neuron Pid ◽  
Lifting System ◽  
Adaptive Pid Control ◽  
Velocity Tracking

The single neutron adaptive PID controller is applied to the angular velocity tracking control of the hydraulic lifting system. The angle velocity tracking control strategy of the lifting process is proposed, and the lifting angle velocity is designed based on the sine acceleration function, and the lifting angle velocity dynamic programming based on the real-time angle is proposed. The single neutron adaptive PID control method is studied, and in order to improve its performance, a method utilizing genetic algorithm to optimize these parameters of single neuron PID controller is presented. The control algorithm is applied to the large mechanical lifting process successfully, and the simulation results show that the control performance of the Adaptive PSD Controller is more effective.

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 PID Control Based on Variable Scale Algorithm in Tar-Ammonia Separation

2010 ◽  
Vol 139-141 ◽  
pp. 1945-1949
Author(s):  
Tian Pei Zhou ◽  
Wen Fang Huang
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Single Neuron ◽  
Control Method ◽  
Optimization Method ◽  
Separation Process ◽  
Control Effect ◽  
Environment Change ◽  
Good Convergence ◽  
Single Neuron Pid

In the process of recycling chemical product in coking object, ammonia and tar were indispensable both metallurgy and agriculture, so the control of separation process for tar-ammonia was one of the most important control problems. Due to the density difference between the tar and ammonia was greater, easier to separate, the control method based on PID was used in field at present. But the control effect of traditional PID was not good because of environment change and fluctuation in material composition. Separation process for tar-ammonia was analyzed firstly, in view of the shortcoming of traditional PID control algorithm, single neuron PID control algorithm based on variable scale method was adopted through using optimization method. Detailed algorithm steps were designed and applied to tar-ammonia separation system. Simulation results show that by comparison with traditional PID algorithm, the algorithm have the following advantages: faster learning speed, shorter adjusted time and good convergence performance.

Design and Research of Energy Saving Control System for Heating Network

2012 ◽  
Vol 591-593 ◽  
pp. 1405-1409
Author(s):  
Hong Xing Sun ◽  
Chuang Gao ◽  
Xin Yan
Keyword(s):  
Pid Control ◽  
Control Algorithm ◽  
Single Neuron ◽  
Heating System ◽  
Loop Model ◽  
Control Effect ◽  
Central Heating ◽  
Single Neuron Pid ◽  
Energy Saving Control ◽  
Controlled Object

In the central heating system, because the controlled object has the characteristics of time-varying, nonlinear, strong coupling and big lag. The traditional single loop model and the conventional PID control algorithm are difficult to react the mechanism and meet the control requirements. Therefore a model of multiplex heating network is established. By comparing the single neuron PID control algorithm with the traditional PID control algorithm, the results show that the single neuron PID control algorithm has a better control effect.

Research and Design of DC Blushless Motor Speed Control System Based on Single Neuron PID Control

2013 ◽  
Vol 347-350 ◽  
pp. 322-326
Author(s):  
Qiao Hong Li ◽  
Fang Hou
Keyword(s):  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Single Neuron ◽  
Speed Control ◽  
Motor Speed ◽  
Brushless Dc ◽  
Brushless Motor ◽  
Speed Control System ◽  
Adaptive Pid Control

The speed regulating system of DC blushless motor was mostly studied. This paper is based on a simplified mathematical model of Brushless DC motor which was consisted of the traditional PID and single neurons. In the Simulink environment, it is established by the control algorithm of single neuron adaptive PID brushless DC motor speed control system closed loop simulation model. From simulation results, the single neuron adaptive PID control system of DC brushless motor has excellent dynamic and static performance. Based on the analysis of DC blushless motor speed control system and simulation results of the neural network control algorithm, hardware of the digital control system for DC brushless motor is designed with control center of high performance microcontroller 80C196KC,which is of single neuron adaptive PID control algorithm.

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.

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.

Sign in / Sign up

Export Citation Format

Share Document