Research on Adaptive Fuzzy PID Dust Collection System

2013 ◽  
Vol 722 ◽  
pp. 437-440
Author(s):  
Zheng Yu Mao ◽  
Jing Sheng Zhang ◽  
Lu Xu Zhang
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Pid Controller ◽  
Time Lag ◽  
Rate Of Change ◽  
Fuzzy Pid ◽  
Collection System ◽  
Fuzzy Pid Control ◽  
Dust Collection ◽  
Adaptive Fuzzy

Aimed at time lag, time variant, serious inertia, nonlinearity problems and the difficulty of PID controller parameters adjusting, the combination of PID control and fuzzy control was put forward, this paper introduces a kind of design of adaptive fuzzy PID dust collection system of constant pressure with regarding the pressure of the deviation and the rate of change of deviation as the input variables in the ventilation pipe. The three parameters of PID controller can be adjusted by establishing the fuzzy control rules and practicing the fuzzy generalize. The experiment simulation and the practical test show that the response of the system with adaptive fuzzy PID control is much faster than the tradition PID control but the overshoot is lower and quickly achieve the steady-state.

The Research on Self-Adaptive Fuzzy PID Controller

2013 ◽  
Vol 373-375 ◽  
pp. 1462-1465
Author(s):  
Bin Liu ◽  
Gang Yao ◽  
Xiao Bing Xiao ◽  
Xu Sheng Yin
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Pid Controller ◽  
Adaptive Fuzzy Control ◽  
Fuzzy Pid ◽  
Matlab Simulation ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Self Tuning ◽  
Self Adaptive

The parameters of the traditional proportional-integral-derivative (PID) controller are hard to automatically adjust when the controlled object changes, which controls ineffective for time-varying, nonlinear system. Combine the fuzzy control and PID control, and use self-adaptive fuzzy control to achieve self-tuning PID parameters online. Using matlab simulation system, the results show that the self-adaptive fuzzy PID control effects have been improved than the conventional PID control.

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.

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

Designing a Fuzzy PID Controller for Brushless DC Motor

2012 ◽  
Vol 588-589 ◽  
pp. 1650-1653
Author(s):  
Yu Hao Qian
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Brushless Dc ◽  
Fuzzy Pid Controller ◽  
Self Adaptive

Based on the mathematical model of the brushless DC motor (BLDCM), a self-adaptive fuzzy PID controller is designed to achieve high-precision speed control of motor by adopting fuzzy control principle, simulation is conducted in MATLAB /SIMULINK, the result shows that the controller can work well with quick response, no overshoot output and high control precision, has strong robustness under the circumstances of various disturbances and parameter variations, whose static and dynamic performance with the self-adaptive fuzzy PID control are both better than conventional PID control.

Intelligent Information Control for Air System

2013 ◽  
Vol 310 ◽  
pp. 502-505
Author(s):  
Jun Zhou
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Air Conditioning ◽  
Information Control ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Air Conditioning System ◽  
Adaptive Fuzzy ◽  
Technical Requirements ◽  
Adaptive Fuzzy Pid Control

PID control has been widely applied in the industrial process control because of its robust and easy realization, but it is difficult to tune the parameters of PID controller, which often leads to oscillation and overshoot. Due to no repetition and random of adaptive fuzzy PID control, the authors propose a method to search for normalization PID controller parameters based on adaptive fuzzy PID control, which can be expected to have higher ability of searching for global optimal PID parameters according to the performance index of control system . The MATLAB simulation of the Adaptive fuzzy PID controller and a PID controller were carried out on the Air Conditioning System temperature. Results showed that: Response time of Adaptive fuzzy PID was 0.46 s., and maximum overshoot didn’t exceed 3.29%.The stability accuracy and rapidity of the system were able to satisfy the Air Conditioning System technical requirements.

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.

The Application of Adaptive Fuzzy PID in the Liquid Level Cascade Control System

2013 ◽  
Vol 846-847 ◽  
pp. 321-324 ◽  
Author(s):  
Le Peng Song ◽  
Hua Bin Wang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Cascade Control ◽  
Liquid Level ◽  
Water Tank ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Adaptive Fuzzy ◽  
Cascade Control System ◽  
Self Adaptive

As liquid level cascade system has the character the issue of non-linearity ,time variability and the overshoot,tradition PID control can not meet the requirement of precise molding system. So devise a self-_ adaptive fuzzy PID control .A self-_ adaptive fuzzy PID control combined PID to control calculate way and faintness to control the advantage of method, this text permits water tank to carry on mathematics model to design the double permit a water tank liquid misty PID string class control system. Matlab/Simulink and fuzzy logic toolbox are simulated to the single loop PID control system,the cascade control system and the cascade control system based on fuzzy self-tuning PID were simulated with Simulink. The analysis and simulation results indicate that the character issue of non-linearity ,time variability and the overshoot of the liquid level cascade control system based on a self-_ adaptive fuzzy PID controller are superior to previous of two methods.

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.

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