scholarly journals A single neuron PID control method based on Smith predictor for active balancing control of rotor with time-delay

2018 ◽  
Vol 20 ◽  
pp. 81-86
Author(s):  
Juan Xu ◽  
Li Zhang ◽  
Yang Zhao ◽  
Yang Lu
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Single Neuron ◽  
Control Method ◽  
Smith Predictor ◽  
Active Balancing ◽  
Single Neuron Pid ◽  
Balancing Control

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.

scholarly journals Rotor dynamic balancing control method based on fuzzy auto-tuning single neuron PID

2017 ◽  
Vol 14 (10) ◽  
pp. 20170130-20170130 ◽  
Author(s):  
Juan Xu ◽  
Yang Zhao ◽  
Zhiyuan Jia ◽  
Jianjun Zhang
Keyword(s):  
Single Neuron ◽  
Control Method ◽  
Dynamic Balancing ◽  
Auto Tuning ◽  
Single Neuron Pid ◽  
Balancing Control ◽  
Rotor Dynamic

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 of Nonlinear PID Control Method for Time Delay Systems

2010 ◽  
Vol 44-47 ◽  
pp. 3839-3843
Author(s):  
Wen Bo Liu ◽  
Meng Xiao Wang
Keyword(s):  
Time Delay ◽  
Pid Control ◽  
Control Method ◽  
Delay System ◽  
Smith Predictor ◽  
Delay Systems ◽  
Time Delay Systems ◽  
Nonlinear Controller ◽  
Time Delay System ◽  
Nonlinear Pid Control

A nonlinear PID control method based on Smith predictor is presented in this paper to control the time delay systems. This method combines the Smith predictor with nonlinear controller. And the simulation study had been done for a first-order time-delay system. The results show that this method offer good static and dynamic characteristics, at the same time its disturbance-rejection and robustness are better.

Adaptive Single Neuron PID Control with Fuzzy and Self-Tuning in Networked Control Systems

2012 ◽  
Vol 235 ◽  
pp. 152-157 ◽  
Author(s):  
Hai Chen Yu ◽  
Cheng Shao ◽  
De Sheng Zhou
Keyword(s):  
Time Delay ◽  
Control Systems ◽  
Pid Control ◽  
Control Algorithm ◽  
Single Neuron ◽  
Networked Control Systems ◽  
Adaptive Performance ◽  
Analysis And Design ◽  
Self Tuning ◽  
Single Neuron Pid

As the varied time-delay caused by the network in NCSs, the analysis and design of NCSs become more difficult. In this paper, the single neuron PID control algorithm is modified by adjusting adaptively the scale factor and learning rate of the neuron with fuzzy rulers subject to NCSs. It is observed from the simulation that the proposed method has a well dynamic and adaptive performance.

scholarly journals An Improved PID Controller for the Compliant Constant-Force Actuator Based on BP Neural Network and Smith Predictor

2021 ◽  
Vol 11 (6) ◽  
pp. 2685
Author(s):  
Guojin Pei ◽  
Ming Yu ◽  
Yaohui Xu ◽  
Cui Ma ◽  
Houhu Lai ◽  
...  
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Pid Control ◽  
Pid Controller ◽  
Experimental Validation ◽  
Control Method ◽  
Smith Predictor ◽  
Constant Force ◽  
Matlab Simulation ◽  
Adjustment Time

A compliant constant-force actuator based on the cylinder is an important tool for the contact operation of robots. Due to the nonlinearity and time delay of the pneumatic system, the traditional proportional–integral–derivative (PID) method for constant force control does not work so well. In this paper, an improved PID control method combining a backpropagation (BP) neural network and the Smith predictor is proposed. Through MATLAB simulation and experimental validation, the results show that the proposed method can shorten the maximum overshoot and the adjustment time compared with traditional the PID method.

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