A Fuzzy Logic Scheme for Lateral Control of an Unmanned Vehicle

2014 ◽  
Vol 1046 ◽  
pp. 250-254
Author(s):  
Yu Fang Zhang ◽  
Xiao Nian Wang ◽  
Ping Jiang ◽  
Jin Zhu
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Dynamic Performance ◽  
Small Error ◽  
Steering Wheel ◽  
Tracking Accuracy ◽  
Lateral Control ◽  
Unmanned Vehicle ◽  
Logic Control

The purpose of unmanned vehicle lateral control is to track a desired trajectory in a small error, in order to achieve a stable tracking under different pavements and wind resistance conditions. This paper presents a vehicle lateral control scheme based on fuzzy logic control. A simplified vehicle lateral dynamics model is first obtained by linearizing the original 6-DOF vehicle model, and then the lateral control is decomposed into two modules: steering wheel angle control and steering wheel speed control. Fuzzy logic control for the two modules is developed and simulated by using CarSim and Simulink. The results demonstrate that the fuzzy controller can achieve a high tracking accuracy with a good dynamic performance.

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.

Interval Type-2 Fuzzy Logic Control of NM70 Shape Memory Actuator

2014 ◽  
Author(s):  
Ireneusz Dominik
Keyword(s):  
Fuzzy Logic ◽  
Shape Memory ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Logic Control ◽  
Interval Type ◽  
Nonlinear Plant

The main aim of this article is to present the usage of type-2 fuzzy logic controller to control a shape memory actuator. To enhance real-time performance simplified interval fuzzy sets were used. The algorithm was implemented in the ATmega32 microcontroller. The dedicated PC application was also built. The fuzzy logic controller type-2 was tested experimentally by controlling position of the shape memory alloy actuator NM70 which despite its small size distinguishes itself by its strength. The obtained results confirmed that type-2 fuzzy controller performed efficiently with a difficult to control nonlinear plant. The research also proved that interval type-2 controllers, which are a simplified version of the general type-2 controllers, are very efficient. They can handle uncertainties without increasing drastically the computational complexity. Experimental data comparison of the fuzzy logic controller type-2 with type-1 clearly indicates the superiority of the former, especially in reducing overshooting.

scholarly journals Optimal Slip Ratio Based Fuzzy Control of Acceleration Slip Regulation for Four-Wheel Independent Driving Electric Vehicles

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Guodong Yin ◽  
Shanbao Wang ◽  
Xianjian Jin
Keyword(s):  
Fuzzy Logic ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Angular Acceleration ◽  
Slip Rate ◽  
Wheel Slip ◽  
Slip Ratio ◽  
Logic Control

To improve the driving performance and the stability of the electric vehicle, a novel acceleration slip regulation (ASR) algorithm based on fuzzy logic control strategy is proposed for four-wheel independent driving (4WID) electric vehicles. In the algorithm, angular acceleration and slip rate based fuzzy controller of acceleration slip regulation are designed to maintain the wheel slip within the optimal range by adjusting the motor torque dynamically. In order to evaluate the performance of the algorithm, the models of the main components related to the ASR of the four-wheel independent driving electric vehicle are built in MATLAB/SIMULINK. The simulations show that the driving stability and the safety of the electric vehicle are improved for fuzzy logic control compared with the conventional PID control.

scholarly journals Fuzzy Logic Control of a Ball on Sphere System

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Seyed Alireza Moezi ◽  
Ehsan Zakeri ◽  
Yousef Bazargan-Lari ◽  
Mahmood Khalghollah
Keyword(s):  
Fuzzy Logic ◽  
Dynamic Systems ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Nonlinear Dynamic Systems ◽  
Underactuated System ◽  
Control Problems ◽  
Logic Control ◽  
Good State ◽  
Simulation Results

The scope of this paper is to present a fuzzy logic control of a class of multi-input multioutput (MIMO) nonlinear systems called “system of ball on a sphere,” such an inherently nonlinear, unstable, and underactuated system, considered truly to be two independent ball and wheel systems around its equilibrium point. In this work, Sugeno method is investigated as a fuzzy controller method, so it works in a good state with optimization and adaptive techniques, which makes it very attractive in control problems, particularly for such nonlinear dynamic systems. The system’s dynamic is described and the equations are illustrated. The outputs are shown in different figures so as to be compared. Finally, these simulation results show the exactness of the controller’s performance.

scholarly journals Power System Stabilization By Fuzzy Set Theory Based Control Of SMES

1970 ◽  
Vol 6 (2) ◽  
pp. 33-41 ◽  
Author(s):  
Md Rafiqul Islam Sheikh ◽  
Rion Takahashi ◽  
Junji Tamura
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Control ◽  
Power System ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Control Method ◽  
Magnetic Energy ◽  
Dynamic Performance ◽  
Superior Performance ◽  
Logic Control

At present fuzzy logic control is receiving increasing emphasis in process control applications. The paper describes the application of fuzzy logic control in a power system that uses a 12- pulse bridge converter associated with Superconductive Magnetic Energy Storage (SMES) unit. The fuzzy control is used in both the frequency and voltage control loops, replacing the conventional control method. The control algorithms have been developed in detail and simulation results are presented. These results clearly indicate the superior performance of fuzzy control during the dynamic period of energy transfer between the power system and SMES unit. Keywords: Fuzzy logic controller; power system dynamic performance; SMES unit. DOI: http://dx.doi.org/10.3329/diujst.v6i2.9343 DIUJST 2011; 6(2): 33-41

scholarly journals An improved 1-φ rectifier system using fuzzy logic control with 3-φ variable frequency drive

2018 ◽  
Vol 7 (2.7) ◽  
pp. 520
Author(s):  
M Kiran Kumar ◽  
SK Almaj ◽  
K S. Srikanth
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Output Frequency ◽  
Variable Frequency Drive ◽  
Dc Voltage ◽  
Motor Current ◽  
Logic Control ◽  
Voltage Ripple

A 3-Φ VFD steam fed from a 1-Φ AC supply. To stop more stresses in the components within the drive and within the input supply,  the drive output power should be restricted. To beat this problem, several VFD makers decided that drive to be de-rated. As often as possible, the drive’s output frequency is limited, supported the dc voltage ripple hence the DC capacitors aren’t overstressed. Through the tradional technique decrement of strain within the DC Capacitors, it doesn’t consider the stresses in other parts of the drive, particularly the diodes at the input and terminal blocks of input. During this paper, brand new fuzzy controller based technique for the protection of the drive the motor   current with FLC is projected. The motor  current is shown to possess info relating the stresses in numerous elements of the VFD together with the diodes at the input, terminal blocks of the input, and therefore the Dc capacitors. The o/p power is projected to be restricted by decreasing the o/p frequency supported the avg and ripple abundancy of the quadrature axis current rather than the dc voltage ripple. To prove this conception, a comparison is made between fuzzy logic controller based technique employing a less power VFD fed from a 1-Φ ac, and the conventional dc voltage ripple based frequency technique.                                                                                                                                                                  

Position Control of 3-DOF Underactuated Manipulators with Last Passive Joint Using Fuzzy Logic Control

2013 ◽  
Vol 373-375 ◽  
pp. 192-196
Author(s):  
Qi Xiao Xia ◽  
Yue Qing Yu ◽  
Zhi Quan Ren
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Logic Controller ◽  
Position Control ◽  
Fuzzy Controller ◽  
Passive Joint ◽  
Logic Control ◽  
Nonholonomic Dynamics ◽  
Underactuated Manipulator ◽  
Underactuated Manipulators

Underactuated manipulator is one kind of second order nonholonomic dynamics systems. How to control this system is still an open problem. This paper proposes a fuzzy strategy to control three DOF underactuated manipulator with a last passive joint. Four measures are selected to construct the fuzzy logic controller. The four measures are divided into two classes; one class is concerning first link, another class concerning the second link. Four fuzzy logic processors are designed to deal with the measure errors, respectively. The four fuzzy logic processors are also divided into two classes according to the two measure classes. Then, the processed results from the four processors are composed to produce control signs to compensate the errors occurring in the manipulator motion. This method simplifies the design of the fuzzy logic controller. Finally, numerical simulation verifies the fuzzy controller.

On the Modelling of a Human Pilot Using Fuzzy Logic Control

2011 ◽  
pp. 148-167
Author(s):  
M. Gestwa ◽  
J.-M. Bauschat
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Logic Control ◽  
Fuzzy Controller ◽  
Tracking Task ◽  
Flight Simulator ◽  
Cognitive Analysis ◽  
Flight Data ◽  
Logic Control ◽  
Control Concept ◽  
Control Behaviour

This chapter discusses the possibility to model the control behaviour of a human pilot by fuzzy logic control. For this investigation a special flight task is considered, the ILS tracking task, and an evaluation pilot has to perform this task in a ground based flight simulator. During the ILS tracking task all necessary flight data are stored in a database and additionally the pilot commands are recorded. The development of the described fuzzy controller (the fuzzy pilot) is based on cognitive analysis by evaluating the recorded flight data with the associated pilot comments. Finally the fuzzy pilot is compared with the human pilot and it can be verified that the fuzzy pilot and the human pilot are based on the same control concept.

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