Error Compensation in Turning Operation of Slender Shaft Using a Fuzzy PID Controller

2010 ◽  
Vol 102-104 ◽  
pp. 392-396
Author(s):  
Jian Liang Guo ◽  
Lian Qing Chen
Keyword(s):  
Error Compensation ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Dimensional Accuracy ◽  
Compensation System ◽  
Fuzzy Pid ◽  
Turning Operation ◽  
Fuzzy Pid Controller ◽  
Machining System ◽  
Conventional Methods

Turning operation of slender shaft poses a great challenge in machining field. It is due to the fact that the accuracy of machined workpiece depends almost completely on the operator’s skill by using conventional methods. To improve the accuracy of slender shaft with less operation skill, this paper presents an error compensation system, which includes a fuzzy PID controller. As a part of the controller, the traditional PID controller is used to control a follower rest for improving the dimensional accuracy. And the fuzzy controller incorporates skilled operators’ knowledge into an automatic machining system. At the end, turning experiments are carried out to verify the efficacy of the error compensation system. The experimental results indicate that the dimensional accuracy of slender shaft using the system is higher and more stable than that by using conventional methods.

Single Degree Vibration Platform Self-Tuning Fuzzy PID Controller Design Based on AMESim

2013 ◽  
Vol 310 ◽  
pp. 518-523
Author(s):  
Zhi Qiang Chao ◽  
Xin Ze Li ◽  
Ai Hong Meng
Keyword(s):  
Hydraulic System ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Simulation Software ◽  
Fuzzy Pid ◽  
Hydraulic Simulation ◽  
Fuzzy Pid Controller ◽  
Single Degree ◽  
Self Tuning

In recent years, hydraulic simulation has become an important means to research hydraulic system, in order to enable the single degree platform vibration curve with better traceability and reach the requirement of the test, this paper represent single degree system platform stimulated by simulation software AMESim, taking the Single degree freedom vibration hydraulic system as an example, MATlab/simulink is applied to the design of the vibration platform system fuzzy PID controller. Through the comparison between the simulation test and traditional PID controller, the designed self-tuning fuzzy controller can control the platform better, with smaller overshoot, faster response, shorter adjusting time, as well as fulfill the permissible accuracy.

Fuzzy PID and Contour Tracking as Applied to Position Control of a Pneumatic Gantry Robot

2013 ◽  
Author(s):  
James Waldie ◽  
Brian Surgenor ◽  
Behrad Dehghan
Keyword(s):  
Pid Controller ◽  
Position Control ◽  
Fuzzy Controller ◽  
Fuzzy Pid ◽  
Pid Algorithm ◽  
Fuzzy Pid Controller ◽  
Future Work ◽  
Fuzzy Pd ◽  
Gantry Robot ◽  
Fuzzy Adaptive

In previous work, the performance of PID plus an adaptive neural network compensator (ANNC) was compared with the performance of a novel fuzzy adaptive PID algorithm, as applied to position control of one axis of a pneumatic gantry robot. The fuzzy PID controller was found to be superior. In this paper, a simplified non-adaptive fuzzy algorithm was applied to the control of both axes of the robot. Individual step results are first shown to confirm the validity of the simplified fuzzy PID controller. The fuzzy controller is then applied to a sinuosoidal tracking problem with and without a fuzzy PD tracking algorithm. Initial results are considered to be very promising. Future work requires developing an adaptive version of the controller in order to demonstrate robustness relative to changing tracking frequencies and changing supply pressures.

Design and Implementation of Fuzzy PID Controller for Brushless DC Motor Control System

2013 ◽  
Vol 432 ◽  
pp. 472-477
Author(s):  
Wei Fan ◽  
Tao Chen
Keyword(s):  
Control System ◽  
Digital Signal Processor ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Digital Signal ◽  
Dc Motor ◽  
Brushless Dc Motor ◽  
Fuzzy Pid ◽  
Brushless Dc ◽  
Fuzzy Pid Controller

This paper presents a robust fuzzy proportional-integral-derivative (PID) controller for brushless DC motor (BLDCM) control system. The hardware circuit of the BLDCM control system is designed and implemented using a digital signal processor (DSP) TMS320LF2407A and a monolithic BLDCM controller MC33035 as the core. Furthermore, a fuzzy PID controller, which combines the advantages of good robustness of fuzzy controller and high precision of conventional PID controller, is employed in the hardware system, thereby yielding a digital, intelligent BLDCM control system. Experimental results have shown that the control system can run steadily and control accurately, and have convincingly demonstrated the usefulness of the proposed fuzzy PID controller in BLDCM control system.

Study on Control Strategies of Semi-Active Air Suspension for Heavy Vehicles Based on Road-Friendliness

2012 ◽  
Vol 452-453 ◽  
pp. 328-333
Author(s):  
Feng He ◽  
Jing Zhao ◽  
Hao Yu Wang
Keyword(s):  
Pid Controller ◽  
Fuzzy Controller ◽  
Control Strategies ◽  
Fuzzy Pid ◽  
Control Effect ◽  
The Road ◽  
Fuzzy Pid Controller ◽  
Air Suspension ◽  
Road Excitation ◽  
Band Limited

Targeting the road-friendliness of vehicles, the paper has analyzed dynamic deformation and dynamic load of tires under different control strategies through co-simulation. A vehicle dynamics model with semi-active air suspension has been made through using Adams, and a PID controller, a fuzzy controller and a fuzzy PID controller have been set in the Matlab to adjust the damping of the suspension, with the road excitation modeled through band-limited white noise. The result shows that the fuzzy PID controller has overcome the shortcomings of the PID controller and the fuzzy controller and a better control effect has been achieved.

Fuzzy Controller Design for Multi-Legged Robot

2011 ◽  
Vol 383-390 ◽  
pp. 7345-7350
Author(s):  
Zhi Yong Tang ◽  
Hai Xiao Zhong ◽  
Zhong Cai Pei ◽  
Yan Hao Bu
Keyword(s):  
Control System ◽  
Real Time ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Controller Design ◽  
High Accuracy ◽  
Dynamics Analysis ◽  
Legged Robot ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

In this paper, we propose a mechanical structure for multi-legged robot. Referring the request of control system, we also made a proper choice on driving means. After dynamics analysis on a single leg of the robot, we make a simulation using ADAMS and get how the torque of each joint is changing when the robot is walking. The model of DC motor is established for the control system. Fuzzy PID controller was used to get real-time response and high accuracy of control system.

Stability Analysis in RECS Integrated Multi-area AGC System with Modified- SOS Optimized Fuzzy Controller

2019 ◽  
Vol 12 (6) ◽  
pp. 532-542 ◽  
Author(s):  
Prakash Chandra Sahu ◽  
Ramesh Chandra Prusty
Keyword(s):  
Power System ◽  
Frequency Response ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Fitness Function ◽  
Automatic Generation ◽  
Settling Time ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Pi Controllers

Background: Automatic Generation Control (AGC) of multi-area nonlinear power system integrated with wind energy based Renewable Energy Conversion System (RECS). Methods: A fuzzy PID controller has been proposed for AGC of a three equal area thermal system integrated with RECS. Different physical nonlinear constraints like Governor Dead Band (GDB) and boiler dynamics are introduced in the model for realization of non linear and realistic of proposed multi area power system. To determine the optimum gain parameter, a Modified Symbiotic Organism Search (M-SOS) algorithm has been used along with a fitness function which based on Integral of Time Multiplied Absolute Error (ITAE). Results: For performance analysis, the performance of proposed M-SOS optimized fuzzy-PID controller is compared with PI, PID and fuzzy PI controllers. For technique comparison, performance of proposed M-SOS technique is compared with original SOS and conventional PSO algorithms. Robustness of proposed controller has also been verified by varying applied load and system parameters. Conclusion: It is observed that M-SOS technique exhibits improved performance over original SOS and PSO algorithms. It is also observed that proposed Fuzzy-PID controller provides better system performance than PI, PID and fuzzy PI controllers. It has been observed that the proposed M-SOS tuned fuzzy PID controller improves settling time of frequency response in area 1 by 11.30%, 15% and 17.75% compared to M-SOS tuned fuzzy PI, PID and PI controllers respectively. Significant improvements in settling time, peak overshoot and peak undershoot of the frequency response in area 2 and tie line power are observed with the implementation this proposed approach.

The Design and Simulation of Scheelite Alkali Autoclave Reactor Fuzzy-PID Controller

2014 ◽  
Vol 599-601 ◽  
pp. 1098-1101
Author(s):  
Xiao Yao Luo ◽  
Bin Chen ◽  
Meng Yu ◽  
Qi Xiong
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Fuzzy Pid ◽  
Matlab Simulation ◽  
Control Effect ◽  
Fuzzy Pid Controller ◽  
Autoclave Decomposition ◽  
Object Of Control ◽  
Autoclave Reactor

In view of the present situation of scheelite smelting technology in China, we analyze the existing equipment and process problems,put forward the technique of mechanical enhancement of scheelite and alkali autoclave decomposition method combining with the temperature, the temperature of reaction kettle as the main object of control, the fuzzy control and PID control combined to design a two-dimensional fuzzy controller, through the MATLAB simulation results show that, the control effect, safety and feasibility of good.

Estimation of the Accuracy of a Control System with a Fuzzy PID Controller Based on the Approximation of the Static Characteristic of the Controller

2021 ◽  
Vol 22 (12) ◽  
pp. 619-624
Author(s):  
Y. A. Bykovtsev ◽  
V. M. Lokhin
Keyword(s):  
Control System ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Piecewise Linear ◽  
Experimental Studies ◽  
Static Characteristic ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Maximum Stability ◽  
Analytical Expressions

The problem of estimating the accuracy of an automatic control system with a fuzzy PID controller is solved. To describe a fuzzy controller, its static characteristic is used, which is approximated by two piecewise-linear and one piecewise-constant sections. This approach makes it possible to study the system as a linear one at each section of the approximated characteristic, and accordingly develop the calculation methods known in control engineering, taking into account the features of the system under consideration. In the article, to calculate the error in the steady state, the theorem on the final value of the original is used. For two different types of second-order control objects — static and astatic — on the basis of this theorem, analytical expressions are obtained that relate the accuracy of the control system with the values of the target and disturbance with a different structure of the controller (P-, PI-, PD-). When conducting experimental studies, the fuzzy PID controller was compared with a linear one tuned by the method of the maximum stability. Research results show that a fuzzy controller ensures the accuracy of the control system is not worse than a linear one, while increasing the dynamics of the system. The analytical expressions presented in the article make it possible to assess the accuracy of a control system with a fuzzy controller and can be used as a technique for adjusting the controller based on the accuracy requirements.

Application of Hybrid Fuzzy PID Control to Auxiliary Workpiece Table

2004 ◽  
Vol 471-472 ◽  
pp. 264-268 ◽  
Author(s):  
Da Wei Zhang ◽  
Yan Ling Tian ◽  
Bing Yan
Keyword(s):  
Pid Controller ◽  
Fuzzy Controller ◽  
Experimental Testing ◽  
Small Range ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Inference Mechanism ◽  
Fuzzy Pid Controller ◽  
Self Tuning ◽  
Hybrid Fuzzy Pid

In order to eliminate the non-linearity of a grinding auxiliary workpiece table, a hybrid fuzzy PID controller has been developed. The two-dimensional fuzzy control with self-tuning factor is utilized to improve the performance. The Max-Min inference mechanism and COG defuzzification method are used to obtain the crisp output of the fuzzy controller. To eliminate the oscillation at balance position, the conventional PID controller is used in the small range of the error and the switch between two controllers can automatically realize according the preset value. Simulation and experimental testing have been carried out to validate the performance of the hybrid fuzzy PID controller.

Design of Compound Fuzzy Controller for Multivariable Systems

2009 ◽  
Vol 16-19 ◽  
pp. 150-154 ◽  
Author(s):  
Xue Ming Zhang ◽  
Gui Xiang Zhang ◽  
Feng Shao ◽  
Qing Jie Yang
Keyword(s):  
Control System ◽  
Pid Control ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Design Method ◽  
Design Procedure ◽  
Fuzzy Pid ◽  
Fuzzy Pid Control ◽  
Fuzzy Pid Controller ◽  
Tuning Rules

The PID controllers can be seen in lots of fields, but some complex control system cannot be controlled to achieve a desired performance index. A design method of the fuzzy PID controller that is based on the fuzzy tuning rules and formed by integrating two above control ideas is proposed in this paper. The design procedure about fuzzy PID control can be divided two steps: the first step is to build the fuzzy tuning rules by analysis, and to obtain the parameters of PID controller by reasoning, and then the control action can be determined by the PID control law. The simulation results and the practical control effects show that the compound fuzzy PID controller has better performance than that of the conventional PID control system and meet the practical demands.

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