scholarly journals Design and Lyapunov Stability Analysis of a Fuzzy Logic Controller for Autonomous Road Following

2010 ◽  
Vol 2010 ◽  
pp. 1-20 ◽  
Author(s):  
Yi Fu ◽  
Howard Li ◽  
Mary Kaye
Keyword(s):  
Fuzzy Logic ◽  
Stability Analysis ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Intelligent Vehicles ◽  
Intelligent Vehicle ◽  
Rule Base ◽  
Control Laws ◽  
Robotic Vehicle ◽  
Road Following

Autonomous road following is one of the major goals in intelligent vehicle applications. The development of an autonomous road following embedded system for intelligent vehicles is the focus of this paper. A fuzzy logic controller (FLC) is designed for vision-based autonomous road following. The stability analysis of this control system is addressed. Lyapunov's direct method is utilized to formulate a class of control laws that guarantee the convergence of the steering error. Certain requirements for the control laws are presented for designers to choose a suitable rule base for the fuzzy controller in order to make the system stable. Stability of the proposed fuzzy controller is guaranteed theoretically and also demonstrated by simulation studies and experiments. Simulations using the model of the four degree of freedom nonholonomic robotic vehicle are conducted to investigate the performance of the fuzzy controller. The proposed fuzzy controller can achieve the desired steering angle and make the robotic vehicle follow the road successfully. Experiments show that the developed intelligent vehicle is able to follow a mocked road autonomously.

Lyapunov approach based design of a gain adaptive interval type-2 fuzzy controller for servo systems

2020 ◽  
pp. 1-19
Author(s):  
Ritu Rani De (Maity) ◽  
Rajani K. Mudi ◽  
Chanchal Dey
Keyword(s):  
Fuzzy Logic ◽  
Stability Analysis ◽  
Fuzzy Controller ◽  
Rule Base ◽  
Performance Study ◽  
Servo Systems ◽  
Lyapunov Approach ◽  
The Stability ◽  
Interval Type

This paper focuses on the development of a stable Mamdani type-2 fuzzy logic based controller for automatic control of servo systems. The stability analysis of the fuzzy controller has been done by employing the concept of Lyapunov. The Lyapunov approach results in the derivation of an original stability analysis that can be used for designing the rule base of our proposed online gain adaptive Interval Type-2 Fuzzy Proportional Derivative controller (IT2-GFPD) for servo systems with assured stability. In this approach a Quadratic positive definite Lyapunov function is used and sufficient stability conditions are satisfied by the adaptive type-2 fuzzy logic control system. Illustrative simulation studies with linear and nonlinear models as well as experimental results on a real-time servo system validate the stability and robustness of the developed intelligent IT2-GFPD. A comparative performance study of IT2-GFPD with other controllers in presence of noise and disturbance also proves the superiority of the proposed controller.

Fuzzy Controller Approach for DC Motor Control on Fishing Rod

2015 ◽  
Vol 2 (1) ◽  
pp. 20-28
Author(s):  
Emmanuel Ade Crisna Putra ◽  
Houtman P. Siregar
Keyword(s):  
Fuzzy Logic ◽  
Transfer Function ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Fuzzy Rule ◽  
Dc Motor ◽  
Step Response ◽  
Rule Base ◽  
Dc Motor Control ◽  
Automation Control

In this paper described the usable and effectiveness of automation control by using fuzzy logic controller forcontrolling the speed of DC motor that will be used on string roller of fishing rod. The transfer function of DCmotor has been obtained. For transfer function, the load of DC motor will be acted as input, and the output is thevelocity of DC motor. The fuzzy rule base then created by trial and error. The step response between fuzzy logiccontroller and without using fuzzy logic controller then obtained and compared. As a result, the fuzzy logic hassuccessfully reduced the overshoot of step response.

Reduced Base Fuzzy Logic Controller for Robot Actuators

2014 ◽  
Vol 555 ◽  
pp. 249-258 ◽  
Author(s):  
Victor Vladareanu ◽  
Paul Schiopu ◽  
Shuang Cang ◽  
Hong Nian Yu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
State Of The Art ◽  
Slight Modification ◽  
Rule Base ◽  
Matlab Simulink ◽  
Current State ◽  
Proposed Model

The paper proposes an innovative type of fuzzy logic controller for robot actuators, building upon the current state of the art fuzzy architectures and various observations from work with Fuzzy Logic and Extenics Theory. This leads to a modified fuzzy controller, with a significantly simpler rule base, which shows comparable results. The effect is achieved by taking advantage of the rule base makeup of a regular linear fuzzy controller. Some slight modification is needed to the controller architecture, which is explained in detail. The rationality and validity of the proposed model are demonstrated through simulation in the Matlab/Simulink environment. The results show that the proposed new controller architecture obtains remarkable results, while having the advantage of increased simplicity in design and setting of parameters. Throughout the paper, opportunities for further improvement and research are highlighted and discussed.

scholarly journals FUZZY-КОНТРОЛЕР ПІДТРИМАННЯ МІКРОКЛІМАТУ В ПРИМІЩЕННІ ЗА ЗНАЧЕННЯМИ ІНДЕКСУ ДИСКОМФОРТУ

2018 ◽  
Vol 9 (4) ◽  
Author(s):  
П. В. Новіков ◽  
О. В. Степанець ◽  
Р. П. Саков
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Control Algorithm ◽  
Fuzzy Logic Controller ◽  
Transfer Functions ◽  
Fuzzy Controller ◽  
Intelligent System ◽  
Rule Base ◽  
Individual Parameter ◽  
Discomfort Index

For microclimate control systems is proposed a control algorithm based on maintaining the desired discomfort index using a fuzzy logic controller. To assess the influence of the environment on humans, it is necessary to determine not only the quantitative value of individual microclimate parameters, but also the result of their overall impact on the human body. The existing complex methods of microclimate control are investigated. An approach to determine the index of discomfort has been analyzed. The values of the discomfort index are divided into ranges, depending on the average comfort sensations in the room for a person. The fundamentals of the theory of fuzzy sets are considered. The fuzzy logic controller is synthesized. A database of rules has been developed based on calculated values of the discomfort index. The intelligent system of automatic maintenance of comfortable microclimate conditions in the room is designed. Based on the calculated values of the discomfort index for all possible variants of the temperature values of dry and wet thermometers, a rule base for the fuzzy controller is built. The computer simulation of the obtained microclimate control system in the room is carried out based on the transfer functions of dry and wet thermometers. The results of mathematical modeling showed the effectiveness of using the proposed control algorithm. The control effect is made after processing the aggregated information directly from two sensors, thereby reducing the number of unnecessary inclusions for small fluctuations of each individual parameter. According to the results of modeling it can be noted compliance with the requirements of the received control system to maintain the desired level of discomfort index in the room, the minimum number of actuator inclusions, no overshoot and energy savings.

scholarly journals Control of Flexible Joint Manipulator via Reduced Rule-Based Fuzzy Control with Experimental Validation

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Mojtaba Rostami Kandroodi ◽  
Mohammad Mansouri ◽  
Mahdi Aliyari Shoorehdeli ◽  
Mohammad Teshnehlab
Keyword(s):  
Fuzzy Logic ◽  
Experimental Validation ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Angular Position ◽  
Rule Base ◽  
Flexible Joint ◽  
Novel Structure ◽  
Flexible Joint Manipulator ◽  
Derivatives Of

A novel structure of fuzzy logic controller is presented for trajectory tracking and vibration control of a flexible joint manipulator. The rule base of fuzzy controller is divided into two sections. Each section includes two variables. The variables of first section are the error of tip angular position and the error of deflection angle, while the variables of second section are derivatives of mentioned errors. Using these structures, it would be possible to reduce the number of rules. Advantages of proposed fuzzy logic are low computational complexity, high interpretability of rules, and convenience in fuzzy controller. Implementing of the fuzzy logic controller on Quanser flexible joint reveals efficiency of proposed controller. To show the efficiency of this method, the results are compared with LQR method. In this paper, experimental validation of proposed method is presented.

Hybrid Neural-Fuzzy Controller for Motorized Robot Arm

2011 ◽  
Vol 403-408 ◽  
pp. 5068-5075
Author(s):  
Fatma Zada ◽  
Shawket K. Guirguis ◽  
Walied M. Sead
Keyword(s):  
Fuzzy Logic ◽  
Design Methodology ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
System Response ◽  
Robot Arm ◽  
Neural Controller ◽  
Hybrid Controller ◽  
Neural Fuzzy ◽  
Transient And Steady State

In this study, a design methodology is introduced that blends the neural and fuzzy logic controllers in an intelligent way developing a new intelligent hybrid controller. In this design methodology, the fuzzy logic controller works in parallel with the neural controller and adjusting the output of the neural controller. The performance of our proposed controller is demonstrated on a motorized robot arm with disturbances. The simulation results shows that the new hybrid neural -fuzzy controller provides better system response in terms of transient and steady-state performance when compared to neural or fuzzy logic controller applications. The development and implementation of the proposed controller is done using the MATLAB/Simulink toolbox to illustrate the efficiency of the proposed method.

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

2019 ◽  
Vol 20 (1) ◽  
pp. 51-62
Author(s):  
Rajmeet Singh ◽  
Tarun Kumar Bera
Keyword(s):  
Fuzzy Logic ◽  
Mobile Robot ◽  
Dynamic Model ◽  
Obstacle Avoidance ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Bond Graph ◽  
Membership Functions ◽  
Current Position ◽  
Dc Motors

AbstractThis work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

scholarly journals DC Motor Speed Control Using Mamdani Fuzzy Logic Based on Microcontroller

Jurnal Teknik ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Sumardi Sadi
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Dc Motor ◽  
Motor Speed ◽  
Logic Control ◽  
Control Command ◽  
Arduino Uno

DC motors are included in the category of motor types that are most widely used both in industrial environments, household appliances to children's toys. The development of control technology has also made many advances from conventional control to automatic control to intelligent control. Fuzzy logic is used as a control system, because this control process is relatively easy and flexible to design without involving complex mathematical models of the system to be controlled. The purpose of this research is to study and apply the fuzzy mamdani logic method to the Arduino uno microcontroller, to control the speed of a DC motor and to control the speed of the fan. The research method used is an experimental method. Global testing is divided into three, namely sensor testing, Pulse Width Modulation (PWM) testing and Mamdani fuzzy logic control testing. The fuzzy controller output is a control command given to the DC motor. In this DC motor control system using the Mamdani method and the control system is designed using two inputs in the form of Error and Delta Error. The two inputs will be processed by the fuzzy logic controller (FLC) to get the output value in the form of a PWM signal to control the DC motor. The results of this study indicate that the fuzzy logic control system with the Arduino uno microcontroller can control the rotational speed of the DC motor as desired.

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