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.

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.

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.

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.

Study of Vice-Steering Control System for Training Car

2011 ◽  
Vol 142 ◽  
pp. 79-82
Author(s):  
Wei Chun Zhang ◽  
Bing Bing Ma ◽  
Xian Bin Du ◽  
Bao Hao Pei ◽  
Jie Chen
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Control System ◽  
Dynamic Characteristics ◽  
Pid Controller ◽  
Fuzzy Controller ◽  
Fuzzy Pid ◽  
Steering Control ◽  
Fuzzy Pid Controller ◽  
System A

Based on analyzing the structure and dynamic characteristics of this system, a dynamical mathematical model is established. To overcome the problems when using fuzzy controller or PID controller respectively and increase precision, a P-fuzzy-PID mode controller and a fuzzy PID controller is designed to control the system. The module of simulink which is a part of MATLAB is used to construct a monolithic mould. The fuzzy logic toolbox is used to construct a fuzzy mould. The results of simulation show that the performance of control becomes better by using this design.

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.

Research on Tyred Machinery Chassis Dynamometer

2013 ◽  
Vol 631-632 ◽  
pp. 1106-1110
Author(s):  
Wei Zhao ◽  
Qiang Wang ◽  
Sheng Li Song
Keyword(s):  
Control System ◽  
System Performance ◽  
Pid Controller ◽  
Fuzzy Pid ◽  
Chassis Dynamometer ◽  
Technical Parameters ◽  
The Road ◽  
Fuzzy Pid Controller ◽  
System A ◽  
Line Measure

In the tyred machinery chassis dynamometer control system, a fuzzy PID controller was used to adjust the exciting current of a DC dynamometer in order to change the resistance load torque, so the requirement of roller load for simulating the run resistance from the road surface was satisfied. A fuzzy PID arithmetic was designed to control the resistance loads, the system performance was improved by simulation. The software of the detection line measure-control system was designed in VB, the technical parameters of the machinery chassis could the automatically detected.

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.

Sign in / Sign up

Export Citation Format

Share Document