International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 04 | Apr 2025
p-ISSN: 2395-0072
www.irjet.net
FPGA-Based Real-Time Bidirectional DC Motor Control with Adaptive Collision Avoidance Using IR Sensors Y.HARI MADHAVA REDDY1,P. SUMAYYA2, K. DINESH KUMAR 3, S.SAI BHANU 4 , SK. SALMA AFRIN5 , K. LAKSHMI SAIKUMAR 6 , V. NAGA NIKHIL7 1Student & KKR & KSR INSTITUTE OF TECHNOLOGY AND SCIENCES 2Student & KKR & KSR INSTITUTE OF TECHNOLOGY AND SCIENCES 3Student & KKR & KSR INSTITUTE OF TECHNOLOGY AND SCIENCES 4Student & KKR & KSR INSTITUTE OF TECHNOLOGY AND SCIENCES
5Student & KKR & KSR INSTITUTE OF TECHNOLOGY AND SCIENCES6 6Student & KKR & KSR INSTITUTE OF TECHNOLOGY AND SCIENCES
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Abstract -
Keywords: FPGA, Bidirectional DC Motor, Collision Avoidance, IR Sensors, Real-Time Control, Pulse-Width Modulation (PWM), Autonomous Systems.
This paper presents a Field-Programmable Gate Array (FPGA)-based real-time bidirectional DC motor control system with adaptive collision avoidance using infrared (IR) sensors. The proposed system ensures efficient and precise motor operation while preventing potential obstacles in dynamic environments. By leveraging the parallel processing capabilities of an FPGA, the design achieves high-speed motor control, low-latency response to obstacles, and real-time adaptability to changing environmental conditions.
1.INTRODUCTION In modern automation and control systems, precise and real-time motor control is a critical requirement for applications such as industrial robotics, autonomous vehicles, conveyor systems, and smart mobility solutions. The ability to efficiently regulate the speed, direction, and responsiveness of a DC motor is essential in ensuring smooth operation, reliability, and safety. However, conventional motor control systems based on microcontrollers and digital signal processors (DSPs) face limitations in terms of latency, computational speed, and real-time adaptability. These constraints hinder their effectiveness in dynamic environments where rapid decision-making is required. To overcome these challenges, this paper introduces an FPGA-based real-time bidirectional DC motor control system with adaptive collision avoidance using infrared (IR) sensors.
The system integrates infrared sensors for collision detection, allowing the motor to dynamically adjust its movement in response to detected obstacles. The bidirectional control mechanism is implemented using pulse-width modulation (PWM) techniques, ensuring smooth speed variations and precise maneuverability. A priority-based decision algorithm processes input signals from the IR sensors and user-defined control switches, dynamically determining the motor’s direction, speed, and operational mode. Unlike conventional microcontroller-based motor control systems, this FPGA-based approach minimizes processing delays and enhances real-time responsiveness. The implementation leverages hardware description language (HDL) programming to achieve efficient logic synthesis, ensuring optimized hardware utilization and scalability. The proposed design is validated through extensive simulations and experimental results, demonstrating its robust performance, low power consumption, and high reliability in practical applications.
Field-Programmable Gate Arrays (FPGAs) have gained prominence in real-time embedded control applications due to their parallel processing capabilities, high-speed execution, and flexibility in hardware reconfiguration. Unlike microcontrollers, which rely on sequential execution of instructions, FPGAs can execute multiple tasks simultaneously, allowing for precise motor control and fast response to environmental changes. By integrating IR sensors, the proposed system is capable of detecting obstacles in real time and dynamically adjusting the motor’s movement to avoid collisions. This approach enhances the system’s safety, efficiency, and operational reliability, making it suitable for applications that require autonomous navigation and intelligent motion control.
This work has broad applicability in autonomous robotic systems, industrial automation, and smart mobility solutions, where precise motor control and real-time obstacle avoidance are critical. The FPGA-based framework provides a foundation for future advancements in intelligent motor control systems by incorporating machine learning techniques and advanced sensor fusion strategies.
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Impact Factor value: 8.315
The system employs pulse-width modulation (PWM) techniques to control the speed and direction of the motor, ensuring smooth acceleration and deceleration. A
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