scholarly journals Expert Control of Mine Hoist Control System

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiuzhi Liu ◽  
Tao Sui
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Expert Knowledge ◽  
Control Effect ◽  
Expert Control ◽  
Simulink Simulation ◽  
Expert Pid ◽  
Mine Hoist

This paper presents a kind of intelligence control algorithm for the mine hoist control system. Firstly, the desired output of the system is described by a speed curve of hoisting process. Then, the structure diagram of the hoist system is constructed, and the expert PID controller is designed based on the model of this control system; the expert knowledge base was established according to the analysis of characteristics in different periods of the hoist process. Finally, the control effect was verified by SIMULINK simulation; by comparing with the result of conventional PID control, expert PID control is improved more safe and suitable for the mine hoist control system.

Design and Implementation of Intelligent Control System for Infrared Shrink Film Machine

2014 ◽  
Vol 532 ◽  
pp. 204-207
Author(s):  
Jiang Zhao ◽  
Wei Ke Fei ◽  
Chong Qing Hao ◽  
Ying Zhang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Control Algorithm ◽  
Physical Simulation ◽  
Simulation System ◽  
Infrared Heating ◽  
Control Effect ◽  
Intelligent Control System ◽  
Technical Requirements ◽  
Adaptive Pid Control

In order to study the control problem of infrared heating shrinkage machine, i.e. Large delay,nonlinearity of the control system, one type of the basic organization and simulation principle of the hardw-in-the-loop simulation system are presented in the given paper, and the simulation model of infrared heating shrinkage machine is discussed. Aiming to solve the problem of traditional PID control algorithm is difficult to get ideal control effect, an adaptive PID control algorithm based on BP neural network is proposed. The object can be better online controlled and adjusted after the algorithm has been applied, meanwhile the requirement of accuracy and reliability will be improved, and quite a lot debugging time will be saved.The results show that the system basically satisfies the technical requirements and provides a good experimental platform.The study is provided with great significance for the realization of the semi-physical simulation system.

scholarly journals Heading Control System Design for a Micro-USV Based on an Adaptive Expert S-PID Algorithm

2018 ◽  
Vol 25 (2) ◽  
pp. 6-13 ◽  
Author(s):  
Runlong Miao ◽  
Zaopeng Dong ◽  
Lei Wan ◽  
Jiangfeng Zeng
Keyword(s):  
Control System ◽  
System Design ◽  
Motion Control ◽  
Pid Control ◽  
Control Algorithm ◽  
Control System Design ◽  
Motion Control System ◽  
Expert Control ◽  
Pid Algorithm ◽  
Heading Control

Abstract The process of heading control system design for a kind of micro-unmanned surface vessel (micro-USV) is addressed in this paper and a novel adaptive expert S-PID algorithm is proposed. First, a motion control system for the micro-USV is designed based on STM32-ARM and the PC monitoring system is developed based on Labwindows/CVI. Second, by combining the expert control technology, S plane and PID control algorithms, an adaptive expert S-PID control algorithm is proposed for heading control of the micro-USV. Third, based on SL micro-USV developed in this paper, a large number of pool experiments and lake experiments are carried out, to verify the effectiveness and reliability of the motion control system designed and the heading control algorithm proposed. A great amount of comparative experiment results shows the superiority of the proposed adaptive expert S-PID algorithm in terms of heading control of the SL micro-USV.

Digital Automatic Control System with PID Controller

1970 ◽  
Vol 110 (4) ◽  
pp. 13-16
Author(s):  
A. Petrovas ◽  
S. Lisauskas ◽  
R. Rinkeviciene
Keyword(s):  
Control System ◽  
Automatic Control ◽  
Design Process ◽  
Automatic Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
General Purpose ◽  
Simulation Results

The design process of digital automatic control system with PID controller is considered. The solution of problems related with implementation of PID control algorithm into general purpose 8-bit microcontroller is discussed. Simulation results demonstrating performance of system are presented. Ill. 4, bibl. 6, tabl. 3 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.110.4.277

Application of Compound PID Control in the DC Servo Motor

2009 ◽  
Vol 16-19 ◽  
pp. 145-149 ◽  
Author(s):  
Xiao Yan Song ◽  
Qing Jie Yang ◽  
Xue Ming Zhang ◽  
Qi Gao Feng
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Pid Control ◽  
Pid Controller ◽  
Design Method ◽  
Servo System ◽  
Fuzzy Pid ◽  
Control Effect ◽  
Fuzzy Pid Controller ◽  
Performance Requirements

Although the traditional PID controller is widely used in many fields, the system parameters varying and external disturbances existing in the DC servo system will cause large overshoot or poor stability. To improve the performance of the PID controller, a compound servo control system combining the conventional PID control and the fuzzy control is presented to meet the demand of a vehicular antenna servo system in this paper. Incorporating the fuzzy control and the conventional PID control, this paper presents a design method of the fuzzy PID controller that is based on the fuzzy tuning rules and formed by integrating two above control ideas. Simulation results are presented to show the efficiency of the proposed controller. The practical control effect shows that the control system that adopts the fuzzy PID controller has better performance than that of the traditional PID control system, and meets the performance requirements of the servo system.

scholarly journals Design and implementation speed control system of DC Motor based on PID control and matlab simulink

2020 ◽  
Vol 11 (1) ◽  
pp. 127
Author(s):  
Salman Jasim Hammoodi ◽  
Kareem Sayegh Flayyih ◽  
Ahmed Refaat Hamad
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Speed Control ◽  
Dc Motor ◽  
Motor Speed ◽  
Matlab Simulink ◽  
Dc Motors ◽  
Electronic Controller

<span>In this paper, we first write a description of the operation of DC motors taking into account which parameters the speed depends on thereof. The PID (Proportional-Integral-Derivative) controllers are then briefly described, and then applied to the motor speed control already described , that is, as an electronic controller (PID), which is often referred to as a DC motor. The closed loop speed control of a Brush DC motor is developed applying the well-known PID control algorithm. The objective of this work is to designed and simulate a new control system to keep the speed of the DC motor constant before variations of the load (disturbances), automatically depending to the PID controller. The system was designed and implementation by using MATLAB/SIMULINK and  DC motor.</span>

WNN Optimizing PID Controller for BLDC Control System

2013 ◽  
Vol 278-280 ◽  
pp. 1529-1532
Author(s):  
Hong Pei Han ◽  
Wu Wang
Keyword(s):  
Neural Network ◽  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
High Efficiency ◽  
Good Control ◽  
Industrial Applications ◽  
Wavelet Neural Network ◽  
Control Effect ◽  
Pid Tuning

Brushless DC motors (BLDC) are widely used for many industrial applications because of their high efficiency, high torque and low volume. This paper presents the PID control for BLDC Motor, because good control effect cannot be acquired by using the traditional PID control in the non-linear variable time servomechanism and it is difficult to tune the parameters and get satisfied control characteristics, some intelligent techniques should be taken. Wavelet Neural Network (WNN) was constrictive and fluctuant of wavelet transform and has self-study, self adjustment and nonlinear mapping functions of neural networks, So, a wavelet neural network self-tuning proportional-integral-derivative (PID) controller was proposed. The structure of WNN and PID tuning with WNN was presented and the equivalent circuit of BLDC and its mathematical models was analyzed, the simulation was taken with new method, the efficiency and advantages of this control strategy was successfully demonstrated which can applied into BLDC control system.

scholarly journals Design of the LADRC control system for gravimetric stabilisation platforms

2021 ◽  
Vol 2113 (1) ◽  
pp. 012018
Author(s):  
Enfan Lin ◽  
Jiangning Xu ◽  
Miao Wu ◽  
Hongyang He
Keyword(s):  
Adaptive Control ◽  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Simulation Experiment ◽  
Control Method ◽  
Control System Design ◽  
Adaptive Control System ◽  
Platform System

Abstract Aiming at the problems of strong non-linearity of gravimeter stabilisation platform system, poor robustness of linear PID control algorithm and non-adaptive control system. This paper designs a LADRC-based gravimetric stabilisation platform control system design and method based on the research of PID controller and ADRC control method, and gives the anti-saturation and anti-noise design applicable to it, and the simulation experiment shows that the method is feasible.

Research on the Fuzzy PID Controller Based on PLC Applied in the Cold Pellet Production

2013 ◽  
Vol 284-287 ◽  
pp. 2291-2295
Author(s):  
Man Chen Xiong ◽  
Ling Long Wang ◽  
Yi Heng Jiang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Fuzzy Controller ◽  
Temperature Control System ◽  
Fuzzy Pid ◽  
Control Effect ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Drying System

Parameter self-setting fuzzy PID control algorithm for control drying temperature is proposed to improve the problem about big fluctuations in temperature and high pellet broken rate of traditional control on Cold pressure ball drying system in this paper, and the controller create intelligence temperature control system through combine fuzzy control and PID control. We establish fuzzy controller, preparation of fuzzy look-up table in PLC and combined with PID control module to realize fuzzy PID control algorithm, through the computer simulation to analyze the fuzzy PID controller control effect.

Application of PID Control Algorithm Based on Improved BP Neural Network to Turntable System

2012 ◽  
Vol 490-495 ◽  
pp. 191-194
Author(s):  
Yang Feng ◽  
Qing Jiu Xu
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Pid Control ◽  
Pid Controller ◽  
Control Algorithm ◽  
Good Control ◽  
Least Square ◽  
Tracking Accuracy ◽  
Control Effect ◽  
Bp Network

Aiming at the problem that traditional PID control algorithm is difficult to get ideal control effect, a PID control algorithm based on improved BP neural network is proposed to improve the performance of turntable system. According to the structure and characteristic of BP neural network, the construction of PID controller and the description of improved BP neural network algorithm are introduced at first. Then, on the basis of the least square method and neural network prediction model of controlled object, the weight adjustment algorithm of PID is improved by replacing the measured values of BP network with calculated forecast output. A mathematical model of turntable control system is established and simulated. Simulation results show that the improved BP neural network PID controller has good control performance, high tracking accuracy and strong system robustness, which can be better applied to turntable system.

Simulation Analysis of Electro-Pneumatic Proportional Fuzzy-PID Control System Based on AMESim/Simulink

2014 ◽  
Vol 945-949 ◽  
pp. 2568-2572
Author(s):  
Si Yuan Wang ◽  
Guang Sheng Ren ◽  
Pan Nie
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Simulation Analysis ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Proportional Control ◽  
Fuzzy Pid Controller ◽  
Design Requirements ◽  
Set Up

The test rig for hydro-pneumatic converter used in straddle type monorail vehicles was researched, and its electro-pneumatic proportional control system was set up and simulated based on AMESim/Simulink. Compared fuzzy-PID (Proportion Integral Derivative) controller with PID controller through fuzzy logic tool box in Simulink, the results indicate that, this electro-pneumatic proportional control system can meet design requirements better, and fuzzy-PID controller has higher accuracy and stability than PID controller.

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