Intelligent Speed Control of DC Motor using Fuzzy Algorithm (original) (raw)

Comparative Analysis of PI, PID and Fuzzy Logic Controllers for Speed Control of DC Motor

2014

DC motor plays an important role in industry. Thus, the speed control of DC motor is a prime task. This paper gives a comparison of the performance of conventional proportional integral (PI), proportional integral derivative (PID) and fuzzy logic controllers (FLC) for speed control of DC motor. A set of rules have been designed for FLC. FLC is an expert knowledge system which improves the result. Thus the comparison of the graphical results so obtained shows that fuzzy logic approach has minimum overshoot, fast response, and minimum transient and steady state parameters. The results so obtained conclude that FLC is more efficient than PI and PID controller.

DC Motor Speed Control: A Case between PID Controller and Fuzzy Logic Controller

Proportional-Integral-Derivative (PID) controllers have gained wide popularity in the control of DC motors. Their performances, though require some degree of manual tuning by the operator, are still satisfactory but a means of auto-tuning is desirable. In this paper, the performance of a select dc motor controlled by a proportional-integral-derivative (PID) controller is investigated. An overshoot is observed with an accompanied large settling time thereby confirming the behavior of a typical PID controller. It is therefore a matter of necessity to tune the PID controller in order to obtain the desired performance. On the other hand, a fuzzy logic based controller applied to the dc motor is investigated. With the application of appropriate expert rules, there is no overshoot and the settling time is within the desired value. With fuzzy logic controller, manual tuning is eliminated and intelligent tuning takes the centre stage with satisfactory performance.

Comparative Study of PID and Fuzzy Controllers for Speed Control of DC Motor

International Journal of Innovative Research in Science, Engineering and Technology, 2014

this paper presents two efficient methods for speed control of a separately excited D.C motor using PID control and fuzzy logic control. The motor was modelled and converted to a subsystem in SIMULINK. The simulation development of the PID controller with the mathematical model of DC motor is done using Ziegler-Nichols method and trial and error method. The PID parameter is tested with MATLAB/SIMULINK program. (FLC) the fuzzy logic controller is designed according to fuzzy rules so that the systems are fundamentally robust. There are 25 fuzzy rules. The FLC has two inputs. One is the motor speed error between the reference and actual speed and the second is change in speed error (speed error derivative).For comparison purpose, PID and Fuzzy controllers have been tested using MATLAB/SIMULINK program for speed under load and no load conditions. The result shows that the Fuzzy controller is the best controller than PID controller. In addition fuzzy logic controller Demonstrates good performance, faster design and work well for high-order and nonlinear and shows the efficiency over the PID controller.

Speed Control of DC Motor Using Fuzzy PID Controller

In this project, we designed a DC motor whose speed can be controlled by a PID controller. The proportional, integral and derivative gains (KP, KI, KD) of the PID controller are adjusted according to Fuzzy logic. First of all, the fuzzy logic controller is designed according to rules so that the systems is basically robust. There are 25 rules for the auto-tuning of each parameter of the PID controller. The FLC (fuzzy logic controller) has two inputs. The first is the motor speed error between the reference (setpoint) and the actual speed. The second is the variation of the speed error (derivative of the speed error). Secondly the output of the FLC is the parameters of the PID controller which are used to control the speed of the DC motor. The study shows that both the precise characters of PID controllers and the flexible characters of fuzzy controllers are present in the fuzzy self-tuning PID controller. The fuzzy auto-tuning approach implemented on a conventional PID structure was able to control the speed of the DC motor. It also improved the dynamic and static response of the system. The comparison between the conventional response and the fuzzy self-tuning response was performed based on the simulation result obtained by MATLAB/SIMULINK. The simulation results show that the designed self-adaptive PID controller achieves good dynamic behavior of the DC motor, perfect speed tracking with short rise and settling times, zero overshoot and steady state error and thus gives better performance compared to the conventional PID controller. We then model the fuzzy PID using simple code on Arduino IDE and perform a practical experiment, to confirm our theorical results.

Speed Control of DC Motor Using Fuzzy Logic Application

2016

Direct current (DC) motors are controlled easily and have very high performance. The speed of the motors could be adjusted within a wide range. Today, classical control techniques (such as Proportional Integral Differential - PID) are very commonly used for speed control purposes. However, it is observed that the classical control techniques do not have an adequate performance in the case of nonlinear systems. Thus, instead, a modern technique is preferred: fuzzy logic. In this paper the control system is modelled using MATLAB/Simulink. Using both PID controller and fuzzy logic techniques, the results are compared for different speed values.

A Comparative Study of Conventional Pid and Intelligent Fuzzy-Pid Fordc Motor Speed Control

Journal of Fundamental and Applied Sciences, 2018

The development of a Self Tuning Fuzzy proportional-integral-derivative (PID) controller was done to be compared with the conventional controller that is being used in a direct current (DC) motor. Simulation study is used to overcome the appearance of nonlinearities and uncertainties in the system with the proposed controller for the armature voltage controlled DC motors. Each parameter of the Fuzzy-PID controller is self tuned using 49 fuzzy rules in the fuzzy logic controller. The proportional, integral and derivative (K P ,K I ,K D ) gains of the PID controller is being tuned by the controller. Different types of membership functions are evaluated in the fuzzy control and the best performance will be used in Fuzzy-PID for comparative analysis with the conventional PID.The FIS editor from MATLAB defines the membership function and the rules. Load disturbances from a variety of speed response and the step response are simulated from different scenarios.The Fuzzy PID has resulted to...

PID and Fuzzy Logic Controllers for DC Motor Speed Control

Communications in Computer and Information Science, 2019

Proportional, integral and derivative (PID) controllers are commonly applied in industrial environments because of their performance and simplicity application in linear systems. On the other hand, Fuzzy logic controllers (FLC) imitate the human knowledge applying a linguistic ideology instead of mathematical calculations. These features make FLC suitable for nonlinear systems by providing an affordable response in terms of speed control. This research proposes a comparative study between PID controller and FLC for separately excited DC motor. Both controllers are tested under different conditions such as overshoot percentage, rise time, torque load disturbance and multiple steps input. Furthermore, this study determines the benefits and drawbacks of each controller when they are evaluated to obtain an appropriated output for DC motor speed control.

IRJET- Intelligent Speed Control of DC Motor using Fuzzy Algorithm

IRJET, 2021

In this paper, an overview of intelligent control technique for the speed control of a direct current (DC) motor has been discussed. Considering the non-linear characteristics of the DC motor and its mechanical variations due to operating conditions, the traditional controllers alone are not enough to give precise control. A more adaptive controller using fuzzy logic is built in this study to realize a better control compared with the current PID controller. It is a technique that auto tunes the PID parameters according to the response of plant. In this the outputs of the fuzzy logic controller are used as dynamic parameters of PID. Simulation results illustrate the practicability of this technique. This article presents a comparative study between Proportional-Integral-Derivative (PID), a modified PID structure called I-PD, Fuzzy Logic Controller (FLC) and Fuzzy PID (F-PID) controllers based on time domain characteristics. The results indicate the supremacy of F-PID over the classical controllers grounded on the transient response analysis.

On Line Tuning of PID Parameters using Fuzzy Logic for DC Motor Speed Control20191222 666 il1wtw

International Journal of Scientific & Engineering Research, 2016

Direct current motors have been used in many practical applications for their good characteristics i.e. variable speed and high staring torque. Most of the applications need variable speed drive with precise speed adjustment at certain values. Form this point of view, robust speed control system is needed. In this research proportional-integral-derivative (PID) control scheme is used for DC motor speed control. PID controller has a simple structure and exhibit robust performance over a wide range of operating conditions. The PID controller gathers the advantages of both proportional integral (PI) and proportional derivative (PD) controllers. The major difficulty with the use of PID controller is the tuning of it is gain parameters i.e. the proportional gain (K P), the integrated gain (K I), and the differential gain (K D). The values of these parameters affect the characteristics of the time response i.e. the rising time (Tr), the settling time (Ts), the peak overshoot (P.O.S) and the steady state error (ess). In the present work PID controller is tuned using two methods :. The First: The conventional method (trial and error) the drawbacks of this tuning method is the long time needed for tuning and the lake of ability to adapt any external influences and disturbances. The second: The intelligent method (Fuzzy Logic) in this method fuzzy logic is used for tuning the gain parameters of the PID controller and to solve the tuning problems in the conventional method. This method allows instantaneous and real time tuning of the controller parameter.