Embedded System Design with ARM Cortex-M Microcontrollers

Ünsalan, Cem; Gürhan, Hüseyin Deniz; Yücel, Mehmet Erkin

doi:10.1007/978-3-030-88439-0

Cited by 4 publications

(2 citation statements)

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“…This study utilizes the STM32F407 microcontroller, equipped with three 12-bit ADC converters and a conversion rate of 1 MHz. The ADC, powered independently between 3.3 and 5.0 volts, allows internal or external reference connections and programmable conversion times across eight discrete ranges (1.5 to 239.5 cycles) [25]. It features 18 multiplexed channels, including 16 for external signals, one linked to an internal temperature sensor, and another to a reference voltage.…”

Section: Microcontroller and Programming Softwarementioning

confidence: 99%

Design and Control of a Laser Cooling System for Wavelength Stabilization of a Monochromatic Light Source

Waiss,

Dalloo

2024

JESA

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Most laser diodes experience fluctuations in intensity, phase, and wavelength, predominantly due to heating from energy conversion to thermal energy and changing ambient temperatures. This study primarily focuses on countering the effects of temperature variations through the design and implementation of a laser diode temperature controller (LDTC) for the fiber optical interferometer system. Additionally, there are other contributing factors, including the injected current, noises, and acoustic disturbances, that play significant roles in these fluctuations. Despite these additional factors, our findings emphasize that temperature remains the principal contributor to these fluctuations. The LDTC developed in this work is cost-effective and rapidly responsive to temperature changes, ensuring precise control over the laser diode's temperature. The findings show the ability of this controller to maintain the temperature of a laser diode at a constant value with a precision (steady-state error) of 0.0013℃ (0.0396℃ without the laser diode) and an average fluctuation of 0.0567℃ (0.0742℃ without the laser diode). Furthermore, the study establishes a relationship between the length of the measurement object and temperature. This laser diode controller was investigated to measure the wavelengthdependent temperature changes at the interferometric point sensor.

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Section: Microcontroller and Programming Softwarementioning

confidence: 99%

Design and Control of a Laser Cooling System for Wavelength Stabilization of a Monochromatic Light Source

Waiss,

Dalloo

2024

JESA

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“…Moreover, embedded software differs from traditional software for different characteristics such as interrupt handling using interrupt service routine (ISR), periodic timer requests, task scheduling, and language dependence. The existing studies [8], [9] show that over 80% of all embedded systems are developed using C procedural and function-oriented language. In many cases, it is assumed that other languages are too memory or resource-intensive to be effectively deployed in bare-metal development.…”

Section: Introductionmentioning

confidence: 99%

Facilitating Reuse of Functions in Embedded Software

2022

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Developing software-intensive embedded systems is a significant challenge as embedded systems have become more complex and dynamic for integrating various constraints (e.g., real-time performance, design, and functional safety). In general, software practitioners reuse code to reduce development time for implementing required functionalities. However, embedded software development still lacks code reuse on a large scale due to its intricate constraints. This paper presents an approach to identifying reusable functions and their relationships from the legacy embedded software for faster development reducing functionality testing time. A python tool is developed to automatically extract the reusable functions and present them in a feature model. The search time for finding reusable functions speeds up when they are placed as features in a feature model. We conducted experiments on three GitHub embedded software projects (elevator, infotainment, and health monitoring systems). The experimental results find that our proposed approach reduces the feature search time by 59.0%, 49.8%, and 74.5%, respectively, compared to the manual searching approach for 50 features.

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