Fuzzy PID Control in the Casting of Hydraulic AGC System Application

2013 ◽  
Vol 694-697 ◽  
pp. 2215-2218
Author(s):  
Xiao Hong Chen ◽  
Xiao Guang Yu ◽  
Yao Yao ◽  
Sheng Jian Xie
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Inference ◽  
Control Parameters ◽  
Control Loop ◽  
Thickness Optimization ◽  
Fuzzy Pid Control ◽  
Loop Control ◽  
Optimization Control ◽  
Fuzzy Adaptive

In view of the existing casting hydraulic AGC control system with time-varying nonlinear and time-delay and problems of the traditional PID control parameters is not easy to adjust,the intelligent fuzzy adaptive PID controller is used for thickness optimization control loop control scheme.Based on the original PID controller combines fuzzy inference function.

Simulation Research on Fuzzy Adaptive PID Control of Variable Pump Control System

2012 ◽  
Vol 220-223 ◽  
pp. 880-883
Author(s):  
Hui Wang ◽  
Zhuo Xu
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Response Speed ◽  
System Response ◽  
Fuzzy Pid Control ◽  
Simulation Research ◽  
Output Pressure ◽  
System Output ◽  
Fuzzy Adaptive

According to the problem of large overshoot in the variable pump constant pressure output, the fuzzy controller and PID controller were combined. The dynamic response of system output pressure was obtained by combining simulation with a fuzzy adaptive PID controller designed in Matlab/Simulink and mechanical hydraulic model established in AMESim. The simulation results show that fuzzy PID control can achieve the goal of system response without overshoot, and response speed is improved further. The anti-interference ability is also stronger.

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.

A novel PID control parameters tuning approach for robot manipulators mounted on oscillatory bases

Robotica ◽  
2007 ◽  
Vol 25 (4) ◽  
pp. 467-477 ◽  
Author(s):  
J. Lin ◽  
Z.-Z. Huang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Low Cost ◽  
Equations Of Motion ◽  
Grey Theory ◽  
Control Parameters ◽  
State Variables ◽  
Relational Analysis ◽  
Parameters Tuning ◽  
Grey Relational

SUMMARYThis research focuses on the issue of dynamic modeling and controlling a robotic manipulator attached to a compliant base. Such a system is known under the name macro–micro system, characterized by the number of control actuators being less than the number of state variables. The equations of motion for a two-link planar elbow arm mounted on an oscillatory base has been presented in this investigation. In order to study the sensitivity of tuning the PID parameters to achieve the desired performance, the Grey relational analysis has first been proposed. Therefore, the aim of this work is to apply Grey theory to optimize parameters for partial states feedback of a PID controller for such a structure. The experimental results of the proposed methodology also show that it is technically and economically feasible to develop a low-cost, reliable, automatic, less time-consuming controller for robotics mounted on oscillatory bases.

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.

Design of PID Controller Based on Compensation with Repetitive Control

2011 ◽  
Vol 105-107 ◽  
pp. 2125-2128
Author(s):  
Hong Liang Guo ◽  
Dong Jie Zhao ◽  
Ling Zhao ◽  
Qing Wang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Combustion Engine ◽  
Permanent Magnet Synchronous Motor ◽  
Tracking Error ◽  
Repetitive Control ◽  
Valve Train ◽  
Accuracy Control ◽  
Loop Control

Valve train is one of important mechanisms in internal combustion engine. The experiment is an important method to study the valve train. In the design of valve train experiment, the Permanent-Magnet Synchronous Motor (PMSM) is used as the driving force to drive the camshaft. PID controller based on compensation with repetitive control is designed to control the PMSM. It can eliminate all periodic errors in closed-loop control. And it has a virtue of nonparametric dependence on its control performance by combining with two control methods. An example has been given and simulation has been made. The simulation result shows that the controller apparently improves the position tracking precision and reduces the tracking error of servo system. So the PID control system based on compensation with repetitive control has a much higher accuracy than the PID control system has. It is fit for high-accuracy control of valve train.

Study of Tobacco-Redrying System Based on Fuzzy PID Control

2012 ◽  
Vol 220-223 ◽  
pp. 1240-1243
Author(s):  
Yu Yu Zhu ◽  
Ya Jun Zhou
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Fuzzy Inference ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Scheme ◽  
Simulation Results ◽  
Performance Target

The process of tobacco-redrying has the characteristics of lagging, uncertainty and being nonlinear, so it is unable to satisfy every performance target only by using the traditional PID controlling method. In response to this reality, this paper, by using the fuzzy inference ability of fuzzy control, proposes a fuzzy PID based control scheme to achieve the online adjustment of the PID parameters in tobacco-redrying process and to make them in the required range. Simulation results show that the controller can effectively control the process of tobacco-redrying.

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.

Research on Fuzzy Pid Control System of Temperatuer for Tertiary Air

2013 ◽  
Vol 341-342 ◽  
pp. 892-895
Author(s):  
Jun Chao Zhang ◽  
Shao Hong Jing
Keyword(s):  
Control System ◽  
Control Theory ◽  
Pid Control ◽  
Pid Controller ◽  
Dynamic Performance ◽  
Effective Control ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Self Tuning

The introduction of the AQC boiler has complex effects on the temperature of Tertiary air, traditional PID is difficult to achieve the effective control. Combined the method of the conventional PID with the fuzzy control theory, a fuzzy self-tuning PID controller is designed. Compared with traditional PID, results of simulation show that the fuzzy PID controller improves not only the adaptability and robustness of the system, but also the system's static and dynamic performance.

Tuning of PID Parameters and Fuzzy Adaptive PID Control of the Hydrostatic Driving System

2011 ◽  
Vol 403-408 ◽  
pp. 5112-5116 ◽  
Author(s):  
Chang Gao Xia ◽  
Chong Cao
Keyword(s):  
Input Signal ◽  
Pid Control ◽  
Pid Controller ◽  
Optimization Method ◽  
Motor Speed ◽  
Driving System ◽  
Displacement Pump ◽  
Adaptive Ability ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

Composed of a variable displacement pump and a constant displacement motor, the hydrostatic driving system is a kind of closed speed control system with adjustable displacement. It is widely used in the field of engineering vehicle and other fields. Based on an analysis of the constitution and mathematical model of the hydrostatic driving system, the present study tuned PID parameters by using the critical proportioning method and the optimization method of NCD respectively. Then a kind of fuzzy adaptive PID controller was designed on the basis of the traditional PID control and the fuzzy control theory. In the controller, fuzzy logic was used to realize online self-tuning of PID parameters according to the motor speed error and its derivative, so that the system could have better adaptive ability and strong disturbance resisting performance. The dynamic simulation was made in MATLAB/SIMULINK. The simulation results show that the optimization method of NCD has better tuning effect and the response performance of the fuzzy adaptive PID controller is better than that of the classic one. Besides, it should be noted that a drawback was found about the fuzzy adaptive PID control. On the basis of fixed scale factors, a group of quantification factors is appropriate for a specific input signal, but for other signals, the response of the system is not so ideal. A method of adjusting quantification factors according to input signal was adopted to solve the above problem. Automatic adjusting of quantification factors was realized, and this could ensure ideal response to all input signals.

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