Research on the Fuzzy PID Speed Control System of Permanent Magnet Linear Synchronous Motor Based on Genetic Algorithm

2014 ◽  
Vol 494-495 ◽  
pp. 1582-1586 ◽  
Author(s):  
Jun Liu ◽  
Qian Wei Xie
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Pid Control ◽  
Linear Time ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Stability Performance ◽  
Control Rules ◽  
Genetic Algorithm Method

Focusing on the non-linear, time-varying, strong coupling and external load disturbance existing in PMLSM, a fuzzy PID controller based on genetic algorithms is designed to control the speed of PMLSM by absorbing the advantages of PID control and fuzzy control, and the genetic algorithm method is used to optimize fuzzy control rules. A simulation experiment was made to compare the effects of traditional PID control and fuzzy PID based on genetic algorithm control by Matlab. The simulation results verify that fuzzy PID control based on genetic algorithm is superior to PID control in dynamic stability performance and speed tracking power.

The Fuzzy PID Control of Resistance Furnace Temperature System Based on Genetic Algorithm

2013 ◽  
Vol 273 ◽  
pp. 678-682 ◽  
Author(s):  
Jing Yan Liu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Pid Control ◽  
Global Optimum ◽  
Fuzzy Pid ◽  
Matlab Simulation ◽  
Resistance Furnace ◽  
Fuzzy Pid Control ◽  
Furnace Temperature ◽  
Control Rules

The resistance furnace temperature system has low accuracy and big overshoots with fuzzy control. The fuzzy PID controller is used to optimize the resistance furnace temperature system, and the design scheme is developed. The fuzzy control and PID control are combined to control the system. If the system’s deviation is large the fuzzy control is adopted, else PID control is adopted. The genetic algorithm is adopted to train the controller’s membership functions, control rules and parameters. The global optimum of the controller’s parameters can be achieved. Matlab simulation results indicate that the resistance furnace temperature system with fuzzy PID control is more dynamic, robust, and highly precise.

Research and Application of Fuzzy Control in Boiler Combustion System Based on ACA

2012 ◽  
Vol 461 ◽  
pp. 642-646
Author(s):  
Chen Wu ◽  
Guo Huan Lou
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Ant Colony Algorithm ◽  
Control Method ◽  
Linear Time ◽  
Control Parameters ◽  
Combustion System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Rules

In the complex control processes of the industrial boiler combustion system with non-linear, time-varying and multivariable, aim at the original control parameters fixed, slow response, delay regulation and other problems, this paper introduces a control method that combines ant colony algorithm with fuzzy PID control, improves the design of fuzzy control rules table and optimizes the PID control parameters. Simulation results show that this control scheme is superior to conventional PID control and fuzzy PID control.

Application of Fuzzy PID Control in Sluice Control

2012 ◽  
Vol 241-244 ◽  
pp. 1248-1254
Author(s):  
Feng Chen Huang ◽  
Hui Feng ◽  
Zhen Li Ma ◽  
Xin Hui Yin ◽  
Xue Wen Wu
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Information Integration ◽  
Pid Controller ◽  
Fuzzy Pid ◽  
Proportional Integral Derivative ◽  
Fuzzy Pid Control ◽  
Tuning Method ◽  
Fuzzy Pid Controller ◽  
Self Tuning

Fuzzy control, based on traditional Proportional-Integral-Derivative (PID) control, is used to improve the management of a hydro-junction’s sluice scheduling. In this study, we combined the PID and Fuzzy control theories and determined the PID parameters of the fuzzy self-tuning method of a hydro-junction’s sluice. A fuzzy self-tuning PID controller and its algorithm were designed. In hydro-junction sluice control, the Fuzzy PID controller can modify PID parameters in real-time, resulting in a more dynamic response. The application of the fuzzy self-tuning PID controller in the CiHuai River project information integration system yielded very good results.

A New Fuzzy PID Control System Based on Fuzzy PID Controller and Fuzzy Control Process

2020 ◽  
Vol 22 (7) ◽  
pp. 2163-2187
Author(s):  
Nguyen Dinh Phu ◽  
Nguyen Nhut Hung ◽  
Ali Ahmadian ◽  
Norazak Senu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Pid Control ◽  
Pid Controller ◽  
Control Process ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller

Development of a Novel Robotic Catheter Manipulating System with Fuzzy PID Control

2012 ◽  
Vol 2 (2) ◽  
pp. 58-77 ◽  
Author(s):  
Xu Ma ◽  
Shuxiang Guo ◽  
Nan Xiao ◽  
Jian Guo ◽  
Shunichi Yoshida ◽  
...  
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Control Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fast Reactions ◽  
Control Rules ◽  
Remote Operations ◽  
Intense Radiation ◽  
Better Than

Manual operation of steerable catheter is inaccurate in minimally invasive surgery, requiring dexterity for efficient manipulation of the catheter, and it exposes the surgeons to intense radiation. The authors’ objectives are to develop a robotic catheter manipulating system that replaces the surgeons with high accuracy. Increasing demands for flexibility and fast reactions in a control method, fuzzy control (FC) can play an important role because the experience of experts can be combined in the fuzzy control rules to be implemented in the systems. They present a practical application of a fuzzy PID control to this developed system during the remote operations and compare with the traditional PID (Proportional-Integral-Derivative Controllers) control experimentally. The feasibility and effectiveness of the control method are demonstrated. The synchronous manipulation performance with the fuzzy PID control is much better than using the conventional PID control method during the remote operations.

Advanced design and tests of a new electrical control seeding system with genetic algorithm fuzzy control strategy

2021 ◽  
pp. 1-10
Author(s):  
Sheng Wang ◽  
Yanhong Sun ◽  
Chen Yang ◽  
Yongchang Yu
Keyword(s):  
Genetic Algorithm ◽  
Control System ◽  
Fuzzy Control ◽  
Electric Drive ◽  
Pid Control ◽  
Fuzzy Pid ◽  
Seeding Rate ◽  
Fuzzy Pid Control ◽  
Transmission Method ◽  
Better Than

In the existing soybean breeding and planting machinery, the power source of the metering device adopts the ground wheel transmission method mostly. However, this power transmission method is likely to cause slippage during the planting operation, which will cause problems such as the increase of the missed seeding index and the increase of the coefficient of plant spacing. It is not conducive for scientific researchers to carry out breeding operations. Aiming at this problem, an electronically controlled soybean seeding system is designed, and the power of the seed metering device is derived from the motor. In order to improve the control accuracy of the electronically controlled seeding system, the precise control of the soybean seeding rate is finally realized. The electric drive soybean seeding system adopts closed-loop control, the motor model of the electric drive seeding system is established, and the transfer function of the motor is obtained. PID control based on a genetic algorithm is adopted, and the corresponding parameters are substituted into the control system simulation model established in MATLAB/SIMULINK. Field verification tests have been carried out on the conventional fuzzy PID control system and the electric drive soybean planter of the fuzzy PID control system based on a genetic algorithm. The result showed that the average of the repeat-seeding parameter is 1.30% better than the average of conventional seeding system (1.40%), the average of the miss-seeding parameter is 1.08% better than the average of conventional seeding system (2.09%) and the average of row-spacing variation parameter is 2.79% better than the average of conventional seeding system (2.34%). In conclusion, the new seeding system is robust obviously. Field trial results show that seeding with Genetic Algorithm Fuzzy control is better.

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.

scholarly journals Fuzzy-PID controller for an energy efficient personal vehicle: Two-wheel electric skateboard

2019 ◽  
Vol 9 (6) ◽  
pp. 5312
Author(s):  
Bambang Sumantri ◽  
Eko Henfri Binugroho ◽  
Ilham Mandala Putra ◽  
Rika Rokhana
Keyword(s):  
Energy Consumption ◽  
Pid Control ◽  
Energy Efficient ◽  
Pid Controller ◽  
Electric Energy ◽  
Fuzzy Pid ◽  
Electrical System ◽  
Fuzzy Pid Control ◽  
Electric Energy Consumption ◽  
Fuzzy Pid Controller

The two-wheeled electric skateboard (TWS) is designed for a personal vehicle. A Fuzzy-PID control strategy is designed and implemented for controlling its motion. Basically, motions control of the TWS is performed by balancing the pitch position of the TWS. Performance of the designed controller is demonstrated experimentally. The Fuzzy algorithm updates the PID gains and therefore it can handle the changing of the TWS load. Contribution of Fuzzy-PID in reducing the electric energy consumption, which is an important issue in electrical system, is also evaluated. The Fuzzy-PID successes to reduce the electric energy consumption of the TWS compared to the conventional PID.

Induction Heating Furnace Temperature Control Based on the Fuzzy PID

2012 ◽  
Vol 217-219 ◽  
pp. 2463-2466 ◽  
Author(s):  
Xue Gang Hou ◽  
Cheng Long Wang
Keyword(s):  
Fuzzy Control ◽  
Temperature Control ◽  
Induction Heating ◽  
Pid Control ◽  
Pid Controller ◽  
Heating Furnace ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Furnace Temperature ◽  
Run Up

Induction heating furnace temperature control is a complex nonlinear hysteretic inertial process, it's difficult to obtain an accurate mathematical model because the temperature and disturb from outside is complicated. The normal PID control algorithm is hard to satisfy the standards of control. The fuzzy PID controller provided in this article is a combination between fuzzy control and the traditional PID control. The Fuzzy control theory is used to setting the ratio, the integral and the differential coefficient of the PID control. In the run-up stage, rapidity is guaranteed, overstrike and the steady-state error is up to the mustard. An example indicates that fuzzy PID control is superior to the normal PID controller.

The Design and Simulation of Control System for Electrical Heating

2013 ◽  
Vol 325-326 ◽  
pp. 1193-1196
Author(s):  
Guo Sheng Xu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Fuzzy Controller ◽  
Electrical Heating ◽  
Temperature Control System ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Fuzzy Pid Controller ◽  
Electric Boiler

In view of the fact that the performance of any conventional PID control can t meet the requirement an electric boiler temperature control system, this paper puts forward a kind of improved algorithm for tuning the PID parameters. an adaptive fuzzy controller with adjusting factor is proposed in this paper. Experimental results illustrate that the adaptive fuzzy PID controller achieved the system performance index. The method of adaptive fuzzy PID control is a ideal method.

Sign in / Sign up

Export Citation Format

Share Document