IoT Driven Servo Motor Control on Raspberry Pi 3B

IoT Driven Servo Motor Control on Raspberry Pi 3B

Mrs.A.KAVITHA

Department of EEE

Sri Bharathi Engineering College for Women,

Kaikkurichi, Pudukkottai, India.

AbstractThis paper presents insight into servo motor control by integrating a servo motor with the Raspberry Pi 3B microcontroller. Utilizing the Blynk app, this approach establishes an interactive platform for precise control. The user-friendly interface, featuring a slider and a submit button within the Blynk app, allows real-time adjustments to the servo motor's position. Building on prior experiences with various microcontrollers, this study extends to the Raspberry Pi, highlighting the immediate responsiveness facilitated by the Blynk app. This concise exploration contributes to the IoT landscape, showcasing efficient servo motor control through a mobile application.

KeywordsServo Motors, Raspberry Pi, IoT (Internet of Things), Micro controller.

1. INTRODUCTION

   Servo motors renowned for their precision and adaptability, play a pivotal role in shaping contemporary technological advancements, especially in robotics, electric vehicles, aeronautics, and satellite systems. Specialized electric motors, servo motors deliver unparalleled control over the angular position of their output shafts. Their applications range from intricately controlling robotic limbs to ensuring precise movements in aeronautical and satellite systems.

   The essence of servo motors lies in their ability to provide meticulous control, making them indispensable in applications where accuracy is paramount. In the dynamic landscape of advancing technology, the demand for servo motors is steadily rising, underscoring the need for a comprehensive understanding of their intricate control requirements.

   At the core of a servo motor's functionality is its capability to maintain a specific position or achieve precise movements with high accuracy. This is accomplished through a closed-loop control system, where the motor continuously receives feedback from an internal sensor or encoder, allowing it to adjust its position in real-time. This feedback loop ensures that the servo motor consistently meets the desired angular position, velocity, and acceleration requirements.

   The working principle involves a sophisticated combination of a DC motor, gearbox, control circuit, and feedback system. The control circuit interprets the desired position signal, compares it with the actual position feedback, and promptly signals the DC motor to adjust its

   rotation in the event of any deviation. This continuous feedback loop is instrumental in ensuring the servo motor's unwavering precision, a factor that profoundly influences the safety, reliability, and overall performance of the systems they drive.

   To meet the demands of precision control, microcontrollers like the Raspberry Pi emerge as critical components. The Raspberry Pi, a credit-card-sized single- board computer, serves as a versatile platform for various embedded computing applications, including servo motor control. The Raspberry Pi's computational capabilities, flexibility, and compatibility make it an ideal choice for orchestrating intricate control systems. In the context of servo motor control, the Raspberry Pi serves as a computational hub, capable of executing complex algorithms to ensure accurate and responsive movements. Furthermore, the use of the Python programming language enhances the Raspberry Pi's effectiveness, providing a user-friendly and powerful toolset for developing control algorithms. Python's simplicity, readability, and extensive libraries make it well-suited for programming servo motor behaviors, allowing researchers and developers to implement and fine-tune precise control strategies with ease.

   The integration of the Internet of Things (IoT) further extends the boundaries of servo motor control. IoT introduces a new dimension, providing a more comfortable and efficient means of managing and monitoring servo motors. This paper explores the symbiotic relationship between servo motors and IoT, offering insights into how interconnected systems enhance the overall control experience, particularly in scenarios where remote and real-time adjustments are essential for optimal performance.

   Additionally, Blynk, a versatile and user-friendly Internet of Things (IoT) platform, stands out as a valuable tool for creating custom mobile applications to control and monitor connected devices. With its simple drag-and-drop interface, Blynk empowers users without extensive programming knowledge to design interactive dashboards. Functioning as a bridge between hardware and mobile devices in the IoT realm, Blynk facilitates seamless communication and control.

   Adding a distinctive layer to the control ecosystem, the Blynk app serves as a medium of interaction, offering user-friendly and intuitive control interfaces. Its adaptability and ease of integration make Blynk a valuable asset in servo motor control, providing

   users with a streamlined and accessible means to interact with and manipulate these critical components. In the following sections, we delve into the interconnected roles of precision control, microcontrollers, IoT, and innovative applications like Blynk in the realm of servo motor dynamics.

2. LITERATURE STUDY

   The integration of Internet of Things (IoT) technologies with servo motor control has garnered significant attention in recent literature, especially in the context of single-board computers like the Raspberry Pi. The following literature study outlines key themes, methodologies, and advancements in IoT-driven servo motor control, with a specific focus on the innovative use of the Blynk platform.

   1. IoT in Servo Motor Control:

      Literature reveals a growing trend in leveraging IoT for enhanced control and monitoring of servo motors. Researchers highlight the potential of real-time data exchange, remote accessibility, and seamless integration with IoT platforms to revolutionize servo motor applications. The integration of IoT technologies aims to bridge the gap between physical devices and the digital realm, opening avenues for efficient and intelligent control mechanisms.

   2. Raspberry Pi in Control Systems:

      The Raspberry Pi, as a versatile and accessible single-board computer, has become a cornerstone in IoT applications. Existing studies underscore its suitability for orchestrating servo motor control systems due to its computational capabilities, GPIO pins, and Linux-based operating system. Researchers delve into the integration of Raspberry Pi in control architectures, emphasizing its role in executing complex algorithms and interfacing with various sensors and actuators.

   3. Servo Motor Control Techniques:

      Literature provides an in-depth exploration of traditional and advanced servo motor control techniques. Researchers delve into PID (Proportional-Integral- Derivative) control, feedforward control, and adaptive control strategies. The focus is on achieving precise and responsive control over servo motors, particularly in dynamic and variable environments.

   4. Blynk as an IoT Platform:

      The Blynk platform has gained prominence for its user-friendly interface and adaptability in IoT projects. Recent literature discusses its unique features, such as drag-and-drop widgets and customizable dashboards, making it an ideal choice for developing IoT applications. Researchers emphasize the ease of integration with various hardware platforms, including the Raspberry Pi, to

      create interactive and remotel accessible control interfaces.

   5. Case Studies and Applications:

      Numerous case studies highlight successful implementations of IoT-driven servo motor control, with a particular emphasis on Raspberry Pi and Blynk integration. These case studies encompass a spectrum of applications, from home automation and smart devices to industrial robotics. Researchers showcase the practicality, efficiency, and scalability of these systems in real-world scenarios.

   6. Challenges and Future Directions:

   Despite the progress, literature acknowledges challenges such as security concerns, latency issues, and the need for standardized protocols in IoT-driven servo motor control. Researchers propose avenues for future research, including the exploration of machine learning algorithms for adaptive control and the development of robust cybersecurity measures for IoT-enabled systems.

   In summary, the literature study underscores the dynamic landscape of IoT-driven servo motor control, particularly on the Raspberry Pi platform, coupled with the innovative integration of the Blynk platform. The synthesis of existing knowledge provides a foundation for the research paper, paving the way for further exploration and contributions in this evolving field.

3. METHODOLOGY

   1. Existing System:

      In current servo motor control setups, the commonly used methods often rely on older approaches that don't quite meet the connectivity and integration needs demanded by today's technology. Many systems still use local interfaces for controlling servo motors, limiting flexibility and making real-time adjustments challenging. Furthermore, the lack of robust Internet of Things (IoT) integration means remote access and advanced control functionalities are often constrained. The user interfaces in existing systems may not be as user- friendly or intuitive, prompting the need for a more modernized system that can adapt to current technological requirements.

   2. Proposed System:

   The proposed system represents a significant advancement in servo motor control by leveraging the computational capabilities of the Raspberry Pi 3B and the Internet of Things (IoT) features of the Blynk platform. This integration aims to overcome the limitations of traditional systems by introducing a dynamic and user- centric control mechanism. The Raspberry Pi acts as a powerful microcontroller, handling complex control algorithms, while Blynk serves as the conduit for seamless

   communication between the user interface and the servo motor. With this system, users can remotely monitor and control the servo motor through an interface embedded within the Blynk app, providing enhanced accessibility and responsiveness. Real-time adjustments, facilitated by IoT integration, extend the system's utility to applications requiring increased adaptability and remote management. This proposed system not only addresses the shortcomings of existing setups but also lays the foundation for a more sophisticated and efficient era of servo motor control within the IoT framework.

4. IMPLEMENTATION

   1. SERVO MOTOR

      The SG90 is a popular model of servo motor known for its compact size and versatility. When interfaced with a Raspberry Pi, the SG90's specifications become relevant for effective integration. The SG90 typically operates on a voltage range of 4.8V to 6V, with a stall torque of approximately 1.8 kg-cm. It has a rotation range of 0 to 180 degrees, making it suitable for various applications requiring controlled and limited movement. When connected to a Raspberry Pi, the GPIO pins can be used to send control signals to the SG90, allowing for precise angular positioning as dictated by the Raspberry Pi's programming. This combination of the SG90 servo motor and Raspberry Pi presents a powerful synergy for applications demanding accurate and programmable motion control.

      Fig.1 SG90 Servo Motor

   2. RASPBERRY PI 3B

      The Raspberry Pi 3, a notable iteration of this popular device, boasts a 1.2GHz quad-core ARM Cortex- A53 processor and 1GB of RAM, offering sufficient computational power for real-time control tasks. Equipped with GPIO pins, the Raspberry Pi facilitates seamless interfacing with external devices, making it an ideal choice for servo motor control. Specifically, for servo motor control using the Blynk app, the GPIO pins serve as the communication bridge between the Raspberry Pi and

      the servo motor. These GPIO pins, when coupled with the Blynk app, enable users to remotely manipulate and monitor servo motor behavior through an intuitive graphical interface. The integration of the Raspberry Pi 3, with its robust specifications, and the Blynk app provides a comprehensive solution for efficient and accessible servo motor control in various applications.

      Fig.2 Raspberry Pi 3B Board

   3. BLYNK – IOT PLATFORM

   Blynk plays a pivotal role in IoT-driven servo motor control using Raspberry Pi. It acts as the interface through which users can remotely manipulate servo motor parameters. By integrating Blynk with Raspberry Pi, users can design a personalized control dashboard on their mobile devices, featuring intuitive elements like sliders and buttons. This allows for real-time adjustments to the servo motor's position and behavior, providing a convenient and efficient means of controlling the servo motor within an IoT framework. The simplicity and adaptability of Blynk contribute significantly to enhancing the user experience and extending the capabilities of IoT applications involving servo motors and Raspberry Pi.

   Fig.3 Circuit Diagram for Hardware Component

   In the implementation phase, the realization of the IoT-driven servo motor control system on the Raspberry Pi 3B was meticulously executed through a structured series of steps outlined in the provided flowchart. The initial step involved the precise physical setup, including the detailed wiring of the SG90 servo motor to the Raspberry Pi 3B using the GPIO pins. To interface with these GPIO pins, critical libraries such as RPi.GPIO and WiringPi were employed, ensuring seamless communication between the Raspberry Pi and the connected servo motor.

5. RESULT ANALYSIS AND DISCUSSION

   The experimental results reveal the successful integration and control of the SG90 servo motor using Raspberry Pi 3 and the Blynk app. The system demonstrated remarkable precision and responsiveness, as evidenced by the smooth adjustments within the servo motor's 180-degree range. Analysis of the Blynk interface, featuring slider button controls, highlighted its intuitive design, allowing users to manipulate the servo motor's rotational position seamlessly.

   Stability was a notable feature throughout the extended operational duration, with no observed crashes or irregularities. User feedback emphasized the user- friendly nature of the Blynk app, affirming its effectiveness in facilitating precise control. Additionally, the system exhibited low-latency network performance, ensuring real-time adjustments, and maintained efficient power consumption levels, contributing to its overall reliability.

   Fig.4 Flowchart of Program Design

   Subsequently, the software components were methodically configured and deployed. Python scripts, capitalizing on the capabilities of both RPi.GPIO and WiringPi libraries, were intricately crafted to establish a robust communication link between the Raspberry Pi 3B and the Blynk cloud server. Git, serving as the version control system, played a pivotal role in maintaining the integrity and versioning of the codebase throughout the entire implementation process.

   Moreover, the Blynk mobile application underwent customization to meet specified requirements, incorporating slider button that seamlessly communicated with the GPIO-controlled servo motor. Rigorous testing, guided by the flowchart and executed in parallel with Git versioning, ensured the reliability and efficiency of the entire system. Dependencies such as RPi.GPIO, WiringPi, and Git were integral components contributing to the successful integration of the IoT-driven servo motor control system. The implementation process, intricately guided by the flowchart, provided a comprehensive and reproducible pathway for deploying an effective IoT- driven servo motor control system using the Raspberry Pi, Blynk, and essential libraries and tools.

   Fig.5 Practical Prototype Model

   Fig.6 Blynk Interface Slider of Servo Motor

   The scalability and flexibility of the setup were evident in its ability to accommodate different servo motor configurations. These findings collectively underscore the practical feasibility and robustness of the integrated system for various applications in robotics and automation. The positive outcomes open avenues for further exploration, such as refining control algorithms and investigating broader applications within the field.

6. CONCLUSION

In conclusion, this study successfully demonstrates the implementation and effectiveness of IoT- driven SG90 servo motor control on Raspberry Pi 3B utilizing the Blynk platform. The experimental results underscore the precision and responsiveness achieved through the Blynk app, offering a user-friendly interface for seamless control. The integration of Blynk and Raspberry Pi in servo motor control, supported by low- latency network performance, showcases the potential for practical applications in the Internet of Things (IoT) domain. This research contributes valuable insights into the synergy between Blynk, Raspberry Pi, and servo motors, laying the groundwork for enhanced control systems in IoT-driven scenarios. The positive outcomes open avenues for further exploration, such as refining control algorithms and investigating broader applications within the field.

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