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.

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.

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-PID Controller for Azimuth Position Control of Deep Space Antenna

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Halima Yakubu ◽  
Suleiman Hussein ◽  
Gokhan Koyunlu ◽  
Essien Ewang ◽  
Sadiq Abubakar
Keyword(s):  
Pid Controller ◽  
Position Control ◽  
Fuzzy Pid ◽  
Deep Space ◽  
Space Antenna ◽  
Fuzzy Pid Controller

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.

scholarly journals Effect of fuzzy PID controller on feedback control systems based on wireless sensor network

2020 ◽  
Vol 10 (3) ◽  
pp. 2416
Author(s):  
Anas A. Hussien ◽  
Mehdi J Marie ◽  
Khalaf S. Gaeid
Keyword(s):  
Control System ◽  
Wireless Sensor Network ◽  
Feedback Control ◽  
Sensor Network ◽  
Pid Controller ◽  
Position Control ◽  
Angular Position ◽  
Wireless Sensor ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller

Wireless Networked control system (WNCS) has an important in all aspects of the life and in the research fields of Engineering. In this article, a real-time implementation of the wireless feedback control system (WFCS) is performed. The stability issue in the closed-loop control system still suffer from noise, disturbances, and need careful considerations to handle it. Three cases to discover the ability of a Fuzzy PID controller to maintain better angular position control system (PCS) is addressed and controlled by a personal computer through a wireless sensor network(WSN) constructed by ZigBee platforms. The practical issues related with the design and implementation of the wireless computerized control system (WCCS) is discussed and analyzed. The simulation results carried out with Matlab/Simulink 2018b. Different parameters effect such as maximum overshoot, sampling frequency, distance and delay time have been studied. These effects on overall system performance would be discussed. Improving the efficient use of ZigBee platform for WFCS. The simulation and experimental results prove the proposed algorithm in the field of wireless 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.

A Study of Vector Control of Induction Machine Considering Iron Loss

2011 ◽  
Vol 268-270 ◽  
pp. 129-137
Author(s):  
Dong Sheng Ding ◽  
Xue Jie Wang ◽  
Xiao Ping Luo
Keyword(s):  
Control System ◽  
Vector Control ◽  
Pid Controller ◽  
Induction Machine ◽  
Environmental Parameters ◽  
Iron Loss ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Vector Control System ◽  
Fuzzy Adaptive

Because of the imperfects of traditional induction control system neglecting iron loss, this paper introduced the parallel equivalent resistance of iron loss, and use new mathematical model of induction machine to establish a more accurate vector control system. However, the increased coupling of parameters in induction machine caused by iron loss is undeserved. We simplified the decoupled system and utilize fuzzy adaptive mechanism to make the speed tuning process more intelligent and robust. The load and non-load experiments show that fuzzy PID controller overcomes the shortcomings of the traditional, reduces the detrimental impacts of iron loss, take advantages of the active impacts from it as well. In the new control system, it adapts to both inner and environmental parameters well, the torque and exciting current are smoother and lower. So, it is extremely meaningful and conducive to the realization of the economical speed tuning.

Research on the Application of the Fuzzy Control Algrithm in the HAPC System

2012 ◽  
Vol 220-223 ◽  
pp. 157-160
Author(s):  
Jing Qing Ma ◽  
Hai Bo Chen
Keyword(s):  
Dynamic Response ◽  
Pid Controller ◽  
Position Control ◽  
Pid Controllers ◽  
Control Methods ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Main Factors ◽  
High Control ◽  
Control Accuracy

The HAPC(Hydraulic Automatic Position Control) requires quick dynamic response and high control accuracy. Based on the research of the HAPC system, I build the HAPC mathematical model, then design both the Conventional PID controller and fuzzy PID controllers, simulate the two control methods using the MATLAB software, analyze the main factors which influence the results. The simulation results show that the fuzzy PID controller has the better effect in the dynamic response and the control accuracy than the former.

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