Application of drive circuit based on L298N in direct current motor speed control system

Yin, Liuliu; Wang, Fang; Han, Shuai; Li, Yuchen; Sun, Hao; Lu, Qingjie; Yang, Cheng Hui; Wang, Quangzhao

doi:10.1117/12.2246555

Cited by 12 publications

(3 citation statements)

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“…The L298N circuit [13] adopts a dual H-bridge configuration for motors, providing high current and voltage capabilities. It can handle currents up to 4A and voltages up to 50V, making it suitable for high-power DC motors, stepper motors, solenoids, and other electronic devices.…”

Section: The Motor Driver Chip L298nmentioning

confidence: 99%

Design of an Intelligent Storage Cabinet System based on STM32

Zheng,

Wu,

Zhong

et al. 2023

Atlantis Highlights in Computer Sciences

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This paper proposes the detailed design of an intelligent storage cabinet system based on STM32. The system includes a control microcontroller, an electronic display screen, capacitive buttons, a temperature and humidity sensor, and a WIFI module, among other measurement and control components. To enhance the users' home living experience, the data system simultaneously uploads information to a cloud platform for real-time monitoring of the temperature and humidity conditions within the storage cabinet. This system design assists households in addressing issues such as the moisture and decay of important paper documents or other items. The system features real-time monitoring of the cabinet's environmental conditions and automatically ventilates and dehumidifies based on the situation. The system also includes remote control functionality through a mobile APP to activate or deactivate the dehumidification and sterilization processes of the storage cabinet. This device enables proper preservation of items and improves people's quality of life. The system incurs relatively low costs and provides a more reasonable solution for the improvement of smart homes.

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Section: The Motor Driver Chip L298nmentioning

confidence: 99%

Design of an Intelligent Storage Cabinet System based on STM32

Zheng,

Wu,

Zhong

et al. 2023

Atlantis Highlights in Computer Sciences

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“…The principle segments utilized for setting up the mechanical vehicle are appeared in Figure 6. These parts are Raspberry Pi III model B, the L298N motor driver, the ultrasonic sensor, the voltage steps down regulator, the Li-Po battery, and the RPi camera [20][21][22][23][24][25]. Figure 6.…”

Section: Car Parts Gathering and Arrangementmentioning

confidence: 99%

Software engineering model based smart indoor localization system using deep-learning

Resan

Croock

2020

TELKOMNIKA

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During the last few years, the allocation of objects or persons inside a specific building is highly required. It is well known that the global positioning system (GPS) cannot be adopted in indoor environment due to the lack of signals. Therefore, it is important to discover a new way that works inside. The proposed system uses the deep learning techniques to classify places based on capturing images. The proposed system contains two parts: software part and hardware part. The software part is built based on software engineering model to increase the reliability, flexibility, and scalability. In addition, this part, the dataset is collected using the Raspberry Pi III camera as training and validating data set. This dataset is used as an input to the proposed deep learning model. In the hardware part, Raspberry Pi III is used for loading the proposed model and producing prediction results and a camera that is used to collect the images dataset. Two wheels' car is adopted as an object for introducing indoor localization project. The obtained training accuracy is 99.6% for training dataset and 100% for validating dataset.

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“…Fig.4Basic H-bridge diagram[18].Table3. Truth table H-bridge circuit[18].Mode Output Input1(IN1) Input2 (IN2) Motor A 0 0 Stop 0 1 Run (Forward) 1 0 Run (Backward) 1 1 Stop…”

mentioning

confidence: 99%

Identification and Speed Control of DC Motor Using Fractional Order PID: Microcontroller

El‐Saadawi¹,

Gouda²,

Elhosseini³

et al. 2020

EJECE

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This paper uses Fractional-order PID control (FOPID) to control the speed of the DC motor. FOPID is more flexible and confident in controlling control higher-order systems compared to classical PID. In this work, the FOPID controller tuning is carried out using different methods ranging from classical techniques to most recent heuristic methods are Fractional Grey wolf Optimization and Nelder-Mead. Moreover, parameter estimation of real-world DC motor is carried out experimentally using Matlab/Simulink interfaced to an Arduino Uno board. The feasibility of FOPID is demonstrated through applications to well-known DC motor case study and the estimated DC motor. Based on ISE, ITE, and ISTE performance measures, the proposed approach provide less settling time, rise time and comparable overshoot compared with existing literature approaches. A robustness assessment with differences in the DC motor components is performed. Simulation finding provide validation of the suggested work and the FOPID controller effectiveness as compared to classical PID controller in terms of robustness and control effect.

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Application of drive circuit based on L298N in direct current motor speed control system

Cited by 12 publications

References 0 publications

Design of an Intelligent Storage Cabinet System based on STM32

Design of an Intelligent Storage Cabinet System based on STM32

Software engineering model based smart indoor localization system using deep-learning

Identification and Speed Control of DC Motor Using Fractional Order PID: Microcontroller

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