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.

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.

Dual Hydraulic Cylinders Synchronized Control Strategy

2014 ◽  
Vol 898 ◽  
pp. 546-549
Author(s):  
Li Ping Liu
Keyword(s):  
Control Strategy ◽  
Pid Control ◽  
Single Neuron ◽  
Control Method ◽  
Synchronization Control ◽  
Depth Study ◽  
Hydraulic Cylinders ◽  
Single Neuron Pid ◽  
Lifting System ◽  
Synchronization Accuracy

Through the double cylinder synchronous lifting system in-depth study presents a master-slave control method and the single neuron PID control strategy for controlling synchronization accuracy. Simulation results show that this method can achieve higher precision synchronization control.

Research on Single Neuron Adaptive PID Control

2012 ◽  
Vol 150 ◽  
pp. 174-177 ◽  
Author(s):  
Yan Hong Zhang ◽  
De An Zhao ◽  
Jian Sheng Zhang
Keyword(s):  
Neural Networks ◽  
Intelligent Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Single Neuron ◽  
Control Parameters ◽  
Control Effect ◽  
The Common ◽  
Single Neuron Pid ◽  
Adaptive Pid Control

As a branch of the intelligent control, neural networks is applied in control more and more widely, the single neuron adaptive PID control algorithm is studied in this paper, and the program is written by MATLAB, the common object of single neuron adaptive PID is simulated, and the effect of single neuron adaptive PID control parameters on control effect is analyzed, experimental results show that the single neuron PID control has more obvious advantages than general PID control.

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.

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