Fuzzy Control Tuning Method of Digital PID Parameters

2012 ◽  
Vol 499 ◽  
pp. 469-473
Author(s):  
Yan Zhong Huo ◽  
Guo Ling Niu ◽  
Shi Jun Ma ◽  
Xu Du
Keyword(s):  
Fuzzy Control ◽  
Pid Controller ◽  
Control Method ◽  
Parameter Tuning ◽  
Control Technology ◽  
Tuning Method ◽  
Parameters Tuning ◽  
Digital Pid ◽  
Controller Performance ◽  
Pros And Cons

As a control method, PID control is the most widely used in industrial processes. However, PID controller parameter tuning of the pros and cons of PID controller performance has been an important factor. Fuzzy control technology is an advanced intelligent control technology, because of its advanced features and easy implementation, it can develop rapidly. This paper describes the theory and method of fuzzy control to realize the dynamic PID controller parameters tuning approach to the PID controller to achieve the best control performance.

Study on Auto-Tuning PID Controller

2014 ◽  
Vol 1037 ◽  
pp. 225-227
Author(s):  
Yin Ping Chen
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Industrial Process ◽  
Parameter Tuning ◽  
Relay Feedback ◽  
Tuning Method ◽  
Common Control ◽  
Auto Tuning ◽  
Tuning Methods

PID control is the most common control method used in process control. The PID control parameters tuning methods are develop constantly. At present, in numerous tuning methods, there are mainly two methods applied better in the practical industrial process. One is based on pattern identification (based on rules); the other is based on relay feedback (based on model). They are collectively referred to as intelligent PID parameter tuning method. This paper studies on the PID parameter auto-tuning methods and introduces the results of the latest research on this subject. Finally, the development direction of auto-tuning PID controller was also prospected.

Design and Simulation of Fuzzy Self-Tuning PID Controller for Two-Link Robot

2012 ◽  
Vol 152-154 ◽  
pp. 1133-1137
Author(s):  
Jian Hu Jiang ◽  
Chao Wu ◽  
Gang Zhang
Keyword(s):  
Pid Controller ◽  
Control Method ◽  
Fuzzy Model ◽  
Parameter Tuning ◽  
Matrix Operation ◽  
Dynamical Equations ◽  
Tuning Method ◽  
Self Tuning ◽  
Actual Response ◽  
Fuzzy Pd

In this paper, fuzzy self-tuning controller is introduced first. The fuzzy model is built according to the experience of PID parameter tuning with fuzzy set theory. Parameter tuning is achieved by use of fuzzy ratiocination and decision according to actual response, which is applied for control towards robot. Mathematical model of two-link robot has been built as well as its geometric and dynamical equations through coordinate transformation and matrix operation. Finally, fuzzy PD controller with self-tuning method is applied to realize control towards robots. Simulation in Matlab has been carried out whose result shows that the control method proposed in this paper has better performance than the traditional ones.

scholarly journals An MEA-Tuning Method for Design of the PID Controller

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongli Zhang ◽  
Lijun Zhang ◽  
Zhiliang Dong
Keyword(s):  
Pid Controller ◽  
Industrial Process ◽  
Optimal Solution ◽  
Design Feature ◽  
Parameter Tuning ◽  
Parallel Structure ◽  
Evolutionary Information ◽  
Tuning Method ◽  
Efficiency And Effectiveness ◽  
Global Optimal

The optimization and tuning of parameters is very important for the performance of the PID controller. In this paper, a novel parameter tuning method based on the mind evolutionary algorithm (MEA) was presented. The MEA firstly transformed the problem solutions into the population individuals embodied by code and then divided the population into superior subpopulations and temporary subpopulations and used the similar taxis and dissimilation operations for searching the global optimal solution. In order to verify the control performance of the MEA, three classical functions and five typical industrial process control models were adopted for testing experiments. Experimental results indicated that the proposed approach was feasible and valid: the MEA with the superior design feature and parallel structure could memorize more evolutionary information, generate superior genes, and enhance the efficiency and effectiveness for searching global optimal parameters. In addition, the MEA-tuning method can be easily applied to real industrial practices and provides a novel and convenient solution for the optimization and tuning of the PID controller.

Research on Adaptive PID Control for Load Simulator with Varying Load

2014 ◽  
Vol 568-570 ◽  
pp. 1031-1035
Author(s):  
Ju Tian ◽  
Yao Chen
Keyword(s):  
Pid Control ◽  
Simple Structure ◽  
Control Method ◽  
Parameter Tuning ◽  
Hardware In The Loop ◽  
Tuning Method ◽  
Hydraulic Load ◽  
Variation Characteristics ◽  
Load Simulator ◽  
Adaptive Pid Control

The electro-hydraulic load simulator is an important equipment for aircraft hardware-in-the-loop simulation. An adaptive PID control method for compensating extraneous torque with simple structure and easy to implement is proposed according to the variation characteristics of load gradient in the load simulator. The control parameter tuning method is also given.

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.

scholarly journals Based on the Multi Variable System Design and Parameter Tuning Method of PID Controller

2017 ◽  
Vol 10 (3) ◽  
pp. 1-14
Author(s):  
Li-Fei Deng ◽  
Yaowu Shi ◽  
Lan-Xiang Zhu ◽  
D. L. Yu ◽  
Rui Zhu
Keyword(s):  
System Design ◽  
Pid Controller ◽  
Parameter Tuning ◽  
Tuning Method ◽  
Variable System

INTEGRATED PID CONTROLLER DESIGN FOR AN UNMANNED AERIAL VEHICLE WITH STATIC STABILITY

2013 ◽  
Vol 54 (3) ◽  
pp. 200-215 ◽  
Author(s):  
R. LI ◽  
Y. J. SHI ◽  
H. L. XU
Keyword(s):  
Fuzzy Control ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Control Method ◽  
Controller Design ◽  
Design Method ◽  
Design Procedure ◽  
Static Stability ◽  
Aerial Vehicle ◽  
Rolling Mode

AbstractThis paper presents an integrated guidance and control (IGC) design method for an unmanned aerial vehicle with static stability which is described by a nonlinear six-degree-of-freedom (6-DOF) model. The model is linearized by using small disturbance linearization. The dynamic characteristics of pitching mode, rolling mode and Dutch rolling mode are obtained by analysing the linearized model. Furthermore, an IGC design procedure is also proposed in conjunction with a proportional–integral–derivative (PID) control method and fuzzy control method. A PID controller is applied in the control loop of the elevator and aileron, and the attitude angle and attitude angular velocity are used as compensation feedback, giving a simple and low-order control law. A fuzzy control method is applied to perform the cross-coupling control of rolling and yawing. Finally, the 6-DOF simulation shows the effectiveness of the developed method.

Application of Fuzzy PID Controller on Mine Local Fan

2014 ◽  
Vol 668-669 ◽  
pp. 450-453
Author(s):  
Mei Zhang
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Fuzzy Pid ◽  
Gas Concentration ◽  
Fuzzy Pid Controller ◽  
The Core ◽  
Adaptive Capability ◽  
Frequency Inverter

Considering the feature of mine local ventilator, the paper proposed a kind of control method combined fuzzy control and PID control to local fan. According to the error and error change of gas concentration, the system automatically adjusted PID controller’s parameters, to having adaptive capability. The monitoring of gas concentration and frequency inverter speed control of fan can be made with the system using TMS320F2407 DSP as the core.

Research on Fuzzy Mathematics in PID Control

2014 ◽  
Vol 608-609 ◽  
pp. 875-879
Author(s):  
Hao Chen ◽  
Zhuo Qi Li
Keyword(s):  
Fuzzy Control ◽  
Pid Control ◽  
Pid Controller ◽  
Control Technology ◽  
Industrial Control ◽  
Pid Algorithm ◽  
Development Cycle ◽  
Short Development Cycle ◽  
Depth Study ◽  
Self Tuning

Aiming at the limitation of traditional PID algorithm in the field of control, the fuzzy control theory and traditional PID control algorithm are combined to realize parameter self-tuning function, a fuzzy self-tuning PID controller, and this algorithm is analyzed in-depth study. It provides a new solution of modern industrial control problem that combining with fuzzy control technology and PID control technology. The FPGA has high integration, short development cycle, the characteristics of strong reusability; fuzzy PID controller has a good practical value and optimistic application prospect based on FPGA.

Parameters Tuning and Performance Analysis of PID Controller for Gas Tank Pressure

2014 ◽  
Vol 716-717 ◽  
pp. 1531-1535
Author(s):  
Jian Zhang ◽  
Song Zhang ◽  
Zhi Hong Dan
Keyword(s):  
Performance Analysis ◽  
Convergence Rate ◽  
Pid Controller ◽  
Parameter Tuning ◽  
Parameters Tuning ◽  
And Performance ◽  
Tank Pressure

In this paper, we firstly analyze the performance of PID controller for pressure of gas tank. Based on the model with the variable of gas mass, we present quantitative relations between PID parameters and convergence rate, overshoot of pressure error. In the following, we further give the principles of parameter tuning for PID controller. Finally, an illustrative example is provided to demonstrate the effectiveness of proposed results.

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