Comparative Speed Control Study Using PID and fuzzy Logic Controller (original) (raw)
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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.
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.
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.
DC motors are widely used in industrial and household applications as they provide benefits of high performance response, high efficiency, high torque and lower volume. This paper proposes the idea of implementing fuzzy logic controller to control the speed of separately excited DC motor. It provides an overview of performance with PID controller and fuzzy logic controller. Though PID controller improves both transients and steady state response characteristics with reduced rise time and steady state error, yet it has limitations of tuning its parameters and unsatisfactory control characteristics. Fuzzy logic can be described simply as computing words and can be designed without knowing the exact mathematical model of the process. Initially these controllers are designed and then tuned to analyze the performance of DC motor. Then the speed response of fuzzy logic is compared with the response achieved by PID controller. The experimental results prove that the control characteristic with fuzzy logic is better than that with the conventional PID controller. The modeling of separately excited DC motor and implementation of the two controllers is performed on software MATLAB/SIMULINK.
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.
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.
Fuzzy Logic Controller versus PID Controller (DC Motor Speed Control
The DC motor is a device that can be found in many applications ranging from industrial applications to home applications. In the use of DC motors the need for speed control and position control arises. Various methods could be applied to the control of DC motor speed, but we shall limit this paper to the use of the PID controller and the Fuzzy Logic Controller (FLC). The speed error signal e(t) and the change in speed error Ce(t) are fed as the input into the FLC. In case of PID the speed error e(t) only is input to generate the control signal u(t). We shall utilize simulations from software like Lab VIEW (Laboratory Virtual Instrument Engineering Workbench and also MATLAB in our analysis and to assert which controller is more preferable.
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.
TECHNOLOGIES AND MATERIALS FOR RENEWABLE ENERGY, ENVIRONMENT AND SUSTAINABILITY: TMREES19Gr
In this paper, a Fuzzy PI Controller used for driving a separately excited DC motor, is compared to Conventional PI Controller, in terms of speed and load transient response of the motor. Further optimization of the Fuzzy PI Controller is performed using different central values for the output fuzzy sets, which are obtained from Simulink's Autotuning function. The effect of the selection of the output fuzzy sets central values is investigated and presented. The logic behind the selection of the Fuzzy Rules is also presented by analyzing the behavior of the DC motor at different operational regions. Performance and robustness results are presented and analyzed.
Intelligent Speed Control of DC Motor using Fuzzy Algorithm
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.