Fuzzy Immune PID Control for 6-DOF Parallel Platform

2011 ◽  
Vol 128-129 ◽  
pp. 890-893
Author(s):  
De Quan Zhu ◽  
Wen Hua Xie ◽  
Lei Sun
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Feedback Mechanism ◽  
Least Square ◽  
Control Precision ◽  
On Line ◽  
Parallel Platform ◽  
Six Degree Of Freedom

To improve the control precision of six degree-of-freedom parallel platform, a fuzzy immune PID control method was presented based on the immune feedback mechanism and fuzzy control theory, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of immune PID control system and the optimal fuzzy proportional parameters. Simulation results demonstrated that the control method designed gets tracking effect with high precision and speed.

Adaptive Fuzzy Immune PID Control for Multi-Joint Robots

2011 ◽  
Vol 58-60 ◽  
pp. 1914-1919
Author(s):  
De Quan Zhu ◽  
Cheng Mao Cao ◽  
Lei Sun ◽  
Mei Zhu
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Robot Manipulator ◽  
Feedback Mechanism ◽  
Least Square ◽  
Adaptive Fuzzy ◽  
Control Precision ◽  
On Line

To improve the control precision of multi-joint robots, a adaptive fuzzy immune PID control method for multi-joint robots was presented based on the immune feedback mechanism and fuzzy control theory, and the parameters of PID controller was optimized with hybrid algorithm. First, least square algorithm was used for off-line optimization to form immune feedback control system. Then, genetic algorithm was used for on-line optimization to get the optimal performance parameters of immune PID control system and the optimal fuzzy proportional parameters. Simulation results of a 2-joint robot manipulator demonstrated that the control method designed gets tracking effect with high precision and speed.

Intelligent Information of TS Fuzzy PID Control System of BLDCM

2013 ◽  
Vol 846-847 ◽  
pp. 313-316 ◽  
Author(s):  
Xiao Yun Zhang
Keyword(s):  
Control System ◽  
Dynamic Model ◽  
Pid Control ◽  
Control Method ◽  
Design Method ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Control Precision ◽  
Simulation Results ◽  
Intelligent Information

This paper presented a new method based on the Fuzzy self - adaptive PID for BLDCM. This method overcomes some defects of the traditional PID control. Such as lower control precision and worse anti - jamming performance. It dynamic model of BLDCM was built, and then design method for TS fuzzy PID model is given, At last, it compared simulation results of PID control method with TS Fuzzy PID control method. The results show that the TS Fuzzy PID control method has more excellent dynamic antistatic performances, as well as anti-jamming performance. The experiment shows that TS fuzzy PID control has the stronger adaptability robustness and transplant.

Design and Simulation of DC Speed Regulating System Based on Fuzzy Control

2012 ◽  
Vol 220-223 ◽  
pp. 1258-1261
Author(s):  
Li Hong Wang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Dynamic State ◽  
State Function ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
On Line ◽  
Start Process ◽  
The Ideal

PID control is adopted in traditional DC speed regulating system. In start process the current super adjustment value is big. When adding load perturbation and voltage perturbation suddenly, its dynamic state function will be decended. Aimming at this problem, a kind of improved system was put forward. The speed modulator used fuzzy PID controller, according to e and ec, the parameters of the modulator can be modified on line. The current modulator adopted integral separable PID control method. The simulation results indicated that the improved system has better dynamic state function and anti- Rao function. Particularly the start current wave closes to the ideal rectangle wave more. So the responding speed of the system can be sped.

The Research of Manipulator’s Hydraulic Driven System on Fuzzy Immune PID Control

2012 ◽  
Vol 220-223 ◽  
pp. 1817-1822
Author(s):  
Zhong Liu ◽  
Deng Liu ◽  
Lan Zhong Guo
Keyword(s):  
Pid Control ◽  
High Speed ◽  
Control Method ◽  
Complex Dynamics ◽  
Control Program ◽  
Feedback Mechanism ◽  
Driven System ◽  
On Line ◽  
Harsh Conditions ◽  
Pilot Valve

A manipulator's hydraulic driven system is an uncertain and nonlinear complex dynamics. Its research is not much at present. The report designed an electro-hydraulic driven control program that high speed on/off valve is worked as the pilot valve for logical cone valve, making up hydraulic driven system of high-power manipulator. For its control problem such as complex, uncertain and nonlinear dynamic, use a fuzzy immune PID control method that the PID controller parameters are on-line tuned by immune feedback mechanism and fuzzy reasoning respectively. With the harsh conditions of the square wave as an input signal, respectively examine response curve of the system using control strategy of the traditional PID and the fuzzy immune PID. Simulation results show that fuzzy immune PID obtains better control performance and robustness, and is superior to the traditional PID. It is fit for control of hydraulic driven system for manipulator.

A Study of PID Control System Based on BP Neural Network

2011 ◽  
Vol 328-330 ◽  
pp. 1908-1911
Author(s):  
Wei Liu ◽  
Jian Jun Cai ◽  
Xi Pin Fan
Keyword(s):  
Neural Network ◽  
Control System ◽  
Conjugate Gradient ◽  
Bp Neural Network ◽  
Pid Control ◽  
Pid Controller ◽  
Steepest Descent ◽  
The Neural Network ◽  
On Line ◽  
New Type

To deal with the defects of the steepest descent in slowly converging and easily immerging in partialm in imum,this paper proposes a new type of PID control system based on the BP neural network, which is a combination of the neural network and the PID strategy. It has the merits of both neural network and PID controller. Moreover, Fletcher-Reeves conjugate gradient in controller can make the training of network faster and can eliminate the disadvantages of steepest descent in BP algorithm. The parameters of the neural network PID controller are modified on line by the improved conjugate gradient. The programming steps under MATLAB are finally described. Simulation result shows that the controller is effective.

Smith Prediction Based on Genetic Algorithm Self-Tuning PID Control

2014 ◽  
Vol 602-605 ◽  
pp. 1186-1189
Author(s):  
Dong Sheng Wu ◽  
Qing Yang
Keyword(s):  
Genetic Algorithm ◽  
Time Delay ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Delay System ◽  
Time Delay System ◽  
Self Tuning ◽  
On Line ◽  
Turning Control

Aiming at the phenomena of big time delay are normally existing in industry control, this paper proposes an intelligent GA-Smith-PID control method based on genetic algorithm and Smith predictive compensation algorithm and traditional PID controller. This method uses the ability of on line-study, a self-turning control strategy of GA, and better control of Smith predictive compensation to deal with the big time delay. This method overcomes the limitation of traditional PID control effectively, and improves the system’s robustness and self-adaptability, and gets satisfactory control to deal with the big time delay system.

PID Control Based Missile Sub-Channel Simulation

2012 ◽  
Vol 433-440 ◽  
pp. 7011-7016 ◽  
Author(s):  
Chao Bo Chen ◽  
Bing Liu ◽  
Ning He ◽  
Song Gao ◽  
Quan Pan
Keyword(s):  
Control System ◽  
Real Time ◽  
Flight Control ◽  
Pid Control ◽  
Pid Controller ◽  
Channel Model ◽  
Control Method ◽  
Flight Control System ◽  
Aerodynamic Control ◽  
The Stability

The accuracy and real-time of modern missile flight control system of traditional aerodynamic can not be satisfied. In this paper a new method is presented to improve the accuracy and real-time of missiles under this condition. First of all, a missile sub-channel model of the dynamic equations and steering gear is established, then based on the established model, using PID controller to control steering gear and three channels of missile pitch, yaw, roll respectively which is called missile sub-channel PID control method, and finally making use of MATLAB/Simulink to complete the simulation. Simulation results show that compared with traditional aerodynamic control system, this method can reduce the response time of aerodynamic missile and enhance the stability of the control system obviously.

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.

PID Parameter Fuzzy Self-Tuning of the Motion Control System

2014 ◽  
Vol 552 ◽  
pp. 187-191
Author(s):  
Meng Xiong Zeng ◽  
Jin Feng Zhao ◽  
Wen Ouyang
Keyword(s):  
Control System ◽  
Motion Control ◽  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Inference ◽  
Inference Method ◽  
Motion Control System ◽  
Control Precision ◽  
Self Tuning ◽  
Fuzzy Control Strategy

In the motion control system, the fuzzy self-tuning of PID parameter is the combination of fuzzy control strategy and traditional PID control, and it is an effective method to improve the control precision. The paper discussed the principle of fuzzy self-adapted PID controller and the parameter fuzzy adjustment, and it realized self-tuning online of PID parameter for the motion control system by using a fuzzy inference method, and the controller was simulated in application of motion control system under the environment of Matlab/Simulink. The simulation result indicated the self-adaptive PID controller enable the motion control system to achieve the satisfied effect.

An Auto-Adaptive GA-PID Control Method Based on CMAC Net

2011 ◽  
Vol 219-220 ◽  
pp. 1139-1144
Author(s):  
Wei Qiang Yue ◽  
Li Qiang Jin ◽  
Chuan Xue Song
Keyword(s):  
Process Control ◽  
Pid Control ◽  
Pid Controller ◽  
Control Method ◽  
Nonlinear Process ◽  
High Accuracy ◽  
Pattern Control ◽  
Nonlinear Process Control ◽  
On Line ◽  
Feed Forward Controller

This paper aimed at solving the difficulty of nonlinear process control by classical PID controller. The author structured a GA-PID controller taking advantage of the multipoint optimizing and fast compute speed of GA, which can get the optimal PID parameters by on-line turning. At the same time, the author introduced a CMAC feed-forward controller which make full use of the high precision to approach nonlinearly object of CMAC. Combine them, a concurrent pattern control method appear, which synthesize advantages of two controllers and is more fit for nonlinear process. The simulation result indicated that the method has high accuracy and good robustness.

Sign in / Sign up

Export Citation Format

Share Document