A Comparison between a Fuzzy and PID Controller for Universal Motor

Zeghoudi, Abdelfettah; Chermitti, Ali

doi:10.5120/18207-9347

Cited by 6 publications

(2 citation statements)

References 6 publications

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“…The control system is made using the Fuzzy Logic Control (FLC) with the help of software MATLAB/ Simulink, then the control is simulated and compared with the Proportional Integral Derivative (PID) controller. The result in [1] shows that FLC has better performance than the PID controller. We have also applied the DC motor because it is the most widely applied actuator in automation systems such as in the control position of an arm robot manipulator [2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Design and Simulation of Fuzzy Logic Based Temperature Control for a Mixing Process in Therapeutic Pool

Ramadhan

Ariyanto

Iskandar

et al. 2018

MATEC Web of Conferences

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Stroke is one cause of the most deaths, in which one way of handling stroke can be done with hydrotherapy. Hydrotherapy is a therapy that is done in the therapeutic pool which is filled with warm water in temperature 31°-34° C. When in the warm water, body burden becomes lighter, so the stroke patients with impaired movement of the body can train the nerves and muscles in order to restore the function of these organs. However, the warm water that is used for the therapy is produced by the heater that requires much electrical energy. This research discussed how to use solar energy to produce hot water using Indirect Evacuated Tube Solar Water Heater systems and make the control system for controlling the mixing process between the hot and cold water by using the Fuzzy Logic Control of the Mamdani method. Therapeutic pool system will be modeled using Simulink. Modeling the mixing process is made on the basis of mass balance and energy balance equations. Then the system will be simulated with interrupted condition and gets set value changes in a particular time. The FLC is successfully reached and maintained steady to a set value. The results will be compared to the performance of the one with Proportional Integral Derivative controller.

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Section: Introductionmentioning

confidence: 99%

Design and Simulation of Fuzzy Logic Based Temperature Control for a Mixing Process in Therapeutic Pool

Ramadhan

Ariyanto

Iskandar

et al. 2018

MATEC Web of Conferences

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show abstract

“…In many engineering applications, using DC (Direct Current) motors under speed control configuration is a common requirement [1,2] because DC motors can provide a high starting torque and are suitable for speed control. Many speed control strategies have been developed for these motors, for example, a modified PI (Proportional-Integral) speed controller was developed in [3], and a comparison between a fuzzy logic and a PID (Proportional-Integral-Derivative) controller for a universal DC motor was reported in [4]. The latter report concluded that fuzzy logic performs better than PID controllers, but they require several fuzzy algorithm rules, which are not easy to conceive.…”

Section: Introductionmentioning

confidence: 99%

Predictive Speed Control of a DC Universal Motor Applied to Monitor Electric Vehicle Batteries

et al. 2023

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This article deals with the design of a simple predictive control algorithm applied to a bidirectional DC-DC power converter for the angular speed control of a DC motor. We used the dynamics of a DC motor but mathematically reduced them to arrive at a simple model that is ideal for our purpose, not only to meet the control objective but also to generate reliable data for further analysis. This predictive control approach is based on the discrete time mathematical model of a DC motor. A huge capacitor to emulate an electric vehicle battery was then successfully connected to our experimental platform. Due to the robustness of the proposed control algorithm, the same predictive control scheme provided sufficient information to monitor the battery’s state. On this basis, and due to the system’s efficiency, it was possible to configure a fault detection scheme in our electric car battery emulator using only classical statistical tools. A PIC18F252 microcontroller was used in our experimental platform to implement our predictive control algorithm. It was then appropriately coupled to the power electronics required by the DC-DC converter to drive the DC motor. Our experimental results proved the excellent performance of the control method and also of the health monitoring system. On the other hand, the main difficulty in achieving our main goal was the realization of discrete control, which had to be as simple as possible while maintaining the control objective and while also being capable of generating reliable data for the health monitoring stage. Thus, the primary contribution of this work was the development of the predictive control of the speed of a universal motor, followed by the modification of the experimental design to simulate an electric car battery and the introduction of a novel statistical method for fault detection.

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Vector Control Strategy of Permanent Magnet Synchronous Motor Based on Fuzzy PID Control

Ji,

Zou,

et al. 2023

Smart Innovation, Systems and Technologies

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A Comparison between a Fuzzy and PID Controller for Universal Motor

Cited by 6 publications

References 6 publications

Design and Simulation of Fuzzy Logic Based Temperature Control for a Mixing Process in Therapeutic Pool

Design and Simulation of Fuzzy Logic Based Temperature Control for a Mixing Process in Therapeutic Pool

Predictive Speed Control of a DC Universal Motor Applied to Monitor Electric Vehicle Batteries

Vector Control Strategy of Permanent Magnet Synchronous Motor Based on Fuzzy PID Control

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