Design Of Tracking System Research Articles

Design and Implementation of Single Axis Solar Tracking System: Utilizing GPS, Astronomical Equations, and Satellite Dish Actuator for Optimal Efficiency

Globally, the focus is on maximizing the energy yield and efficiency of PV systems as an essential renewable energy source. Different methods have been proposed to achieve this goal. Where the sun’s location in the sky is changed during the day, a tracking mechanism has been proposed as a promising technology to harness the maximum amount of solar radiation by PV system as compared to the fixed panels. In this study, the design and implementation of a polar single-axis tracking system is presented to improve the energy efficiency of PV system through angular variation during the day using the proposed tracking system. This is achieved by interconnecting some devices that include GPS sensors and satellite dish actuators as the main components that are managed and controlled using astronomical equations. The designed system is tracked in a discrete manner that can be adjusted automatically during the day related to each degree change of azimuth angle of the sun from sunrise to sunset. The system has been field tested in Sulaymaniyah, Iraq, to evaluate its performance in different weather conditions and compare it with a fixed PV system. The test results for the clear sky indicated that the increased amount of energy production for the tracking system is 36.6% as compared with the stationary panel. Whereas, for a mostly cloudy day the measured amount of increase was 18.5%. This improvement of the harnessed energy for PV systems is important to make the system more efficient and sustainable.

Particle Filter Tracking System Based on Digital Zoom and Regional Image Measure

To address the challenges of low accuracy and the difficulty in balancing a large field of view and long distance when tracking high-speed moving targets with a single sensor, an ROI adaptive digital zoom tracking method is proposed. In this paper, we discuss the impact of ROI on image processing and describe the design of the ROI adaptive digital zoom tracking system. Additionally, we construct an adaptive ROI update model based on normalized target information. To capture target changes effectively, we introduce the multi-scale regional measure and propose an improved particle filter algorithm, referred to as the improved multi-scale regional measure resampling particle filter (IMR-PF). This method enables high temporal resolution processing efficiency within a high-resolution large field of view, which is particularly beneficial for high-resolution videos. The IMR-PF can maintain high temporal resolution within a wide field of view with high resolution. Simulation results demonstrate that the improved target tracking method effectively improves tracking robustness to target motion changes and reduces the tracking center error by 20%, as compared to other state-of-the-art methods. The IMR-PF still maintains good performance even when confronted with various interference factors and in real-world scenario applications.

Enhancing solar energy collection with the implementation of a dual-axis tracking system

Abstract This paper describes the design and control of a two-axis solar tracking system that is unique in integration and uncomplicated in structure. Concerning the accumulation of solar energy, the system adopts a Solar Photovoltaic (SPV) power plant model. Theoretical analysis of the output of the system including the impact of the solar radiation was also done and a comparison was made with a fixed axis SPV station provided with fixed stand tilt at 30° south. As shown in the outcomes, the efficiency of the proposed dual-axis tracking system is much higher than that of the keeper-stationary positioning scheme. These results proved the hypothesis of the effectiveness of the proposed SPV system from both experimental and theoretical positions. A comparison of data indicated that the tracking system tapped much more solar energy than the fixed system. Consequently, this research aims at transforming and investigating the feasibility of small and medium scale SPV power uses employing dual-axis solar tracking systems.

Design and Implementation of a Dual-Axis Solar Tracking System with IoT-Enhanced Monitoring Using Arduino

The position of the sun varies over the day and with the seasons, making it difficult for conventional fixed solar panel systems to achieve optimum energy production. By reorienting the panels to face the sun, solar tracking systems solve this problem. This study suggests a dual-axis solar tracker system that continuously adjusts the panels to stay perpendicular to sunlight in order to maximize energy capture. The system uses sensors to monitor the sun's elevation and azimuth angles. Light sensors, motor controllers, microcontrollers, control algorithms, and an Internet of Things (IoT) monitoring system are some of the system's essential parts. The microprocessor determines the ideal angles for panel alignment based on the location of the sun as detected by the light sensors. The motor driver then adjusts the panels appropriately. The sun's position is accurately and smoothly tracked using dual-axis tracking systems, which employ sensors to detect solar position and actuators controlled by sophisticated algorithms to adjust the panels accordingly. Real-time parameter monitoring of the solar panel is done using an IoT-enabled webpage. The study's findings show that the dual-axis solar tracker system performs noticeably better in terms of energy capture efficiency than fixed installations, especially in areas with high solar incidence angles and fluctuating sunshine.

Hardware implementation of Firefly algorithm-based maximum power point tracking on Arduino

In this paper, we present the design and implementation of a Firefly Algorithm-based Maximum Power Point Tracking (MPPT) system on an Arduino platform, aimed at optimizing the performance of photovoltaic systems under variable environmental conditions, particularly partial shading. The Firefly Algorithm was chosen for its ability to efficiently locate the global maximum power point in the presence of multiple local maxima caused by non-uniform irradiance. The experimental setup utilized a Boost converter controlled by the Arduino, dynamically adjusting the duty cycle to maintain the PV system at its optimal operating point. Results demonstrated the system's effectiveness in responding to changes in solar irradiance, ensuring consistent maximum power output. Building on this, our research highlights the use of low-cost hardware like Arduino for implementing advanced MPPT algorithms, bridging the gap between theoretical research and practical applications. The study emphasizes that even with limited resources, significant gains in efficiency can be achieved in renewable energy systems. The findings suggest that using such a platform not only reduces costs but also enhances the accessibility of advanced MPPT technologies in real-world applications, making them a viable option for broader adoption.

Tracking System for Living Beings and Objects: Integration of Accessible Mathematical Contributions and Graph Theory in Tracking System Design

This paper presents a theoretical framework for a tracking system, wherein we generalize the formulation of a tracking system de- signed for living beings and objects. Many tracking systems are typically developed within specific frameworks, either for tracking in limited or unlimited space. The latter often relies on technical tools dedicated to tracking living beings or objects. In this study, we propose a system theory that formulates the task of tracking both living beings and ob- jects. Graphical modeling is widely employed in tracking to establish correct connections between the elements to be tracked and other com- ponents in the system. However, basing a tracking system on graphs in both its theoretical and practical aspects remains the optimal method for achieving a high-performing, relevant, and adaptable system in vari- ous situations. This paper introduces a tracking system based on graph learning and hypergraphs, fully leveraging direct and indirect relations while considering the order between multiple system links. Tracking is thus formulated as a search problem on graphs and hypergraphs, with vertices representing the elements of the system (living beings or ob- jects), and edges representing the types of connections between these elements. We define a law governing the relationships between the ver- tices, managing the shared data between the elements of the system and other processes. Furthermore, examples of single and multi-context track- ing situations demonstrate that the proposed system, in its theoretical foundation, outperforms existing systems.

Design and application of UAV single target tracking system based on YOLOv5

In aerial reconnaissance, pursuit, and post-disaster search and rescue, rotorcraft UAVs are valued for their agility. A key challenge is target tracking in complex environments with no prior information, dense obstacles, GNSS signal loss, and occluded targets. This paper introduces a YOLOv5-based UAV tracking system to address detection and path planning. The quadrotor UAV model ensures stable flight through mathematical modeling and simulation. YOLOv5 enhances detection performance with real-time tracking. Feedback control enables autonomous obstacle avoidance and target tracking. Results show adaptability and robustness, supporting reconnaissance and rescue missions effectively.

The Design of Sound Source Location and Tracking System Based on TDOA

The Design of Sound Source Location and Tracking System Based on TDOA

An improved cubature Kalman filter state prediction method based on the design of active denial tracking system.

In this paper, an improved CKF (Cubature Kalman Filter) target tracking method is adopted to solve the tracking and pointing problem in the field of the Active Denial System. The math model of the system is built and the precision requirement is analyzed. The improved CKF method is input as the feedforward compensation for system control to improve the system tracking performance. In the process of the iterative CKF algorithm, nonlinear means are used. The method makes full use of measurement information and estimates the target velocity acceleration model parameters through the neural network, which is used as the input of the CKF to modify the process parameters of CKF and improve the state estimation accuracy. At the same time, the limited lower bound method is used to ensure that the gain reaches the lower bound bottom line of the precision demand, so that it does not tend to zero with time, so as to avoid affecting its rapid response ability during maneuvering and so that the prediction error is also controlled within the range of the precision demand. The simulation and experimental results show the superiority of the method and make the system fully meet the design requirements.

LCC-based approach for design and requirement specification for railway track system

AbstractLife cycle cost (LCC) analysis is an important tool for effective infrastructure management. It is an essential decision support methodology for selection, design, development, construction, maintenance and renewal of railway infrastructure system. Effective implementation of LCC analysis will assure cost-effective operation of railways from both investment and life-cycle perspectives. A major setback in the successful implementation of LCC analysis by infrastructure managers is the availability of relevant, reliable, and structured data. Different cost estimation methods and prediction models have been developed to deal with this challenge. However, there is a need to include condition degradation models as an integral part of LCC model to account for possible changes in the model variables. This article presents an approach for integrating degradation models with LCC model to study the impact of change in design speed on key decision criteria such as track possession time, service life of track system, and LCC. The methodology is applied to an ongoing railway investment project in Sweden to investigate and quantify the impact of design speed change from 250 to 320 km/h. The results of the studied degradation models show that the intended change in speed corresponds to correction factor values between 0.79 and 0.96. Using this correction factor to compensate for changes in design speed, the service life of ballasted track system is estimated to decrease by an average of 15%. Further, the expected value of LCC for the route under consideration will increase by 30%. The outcome of this study will be used to support the design and requirement specification of railway track system for the project under consideration.

High-Precision Pointing and Tracking System Design for Near-Space Balloon-Based Optical Observation

Near-space high-altitude balloon-based platforms have a series of advantages and provide superior conditions for optical observation. In order to ensure the stability of the optical axis of the optical detection load and stable tracking of the target, a near-space high-altitude balloon-based high-precision pointing and tracking system was designed, which can compensate for changes in the pitch angle and azimuth angle of the platform during flight. The system includes a primary platform stable pointing system and a secondary precise tracking system. In the finished flight experiment, the primary platform pointing system and secondary precise tracking system on the balloon-based observation platform worked normally, providing a guarantee for the coronagraph’s stable tracking and detection of the sun. The primary platform pointing system can realize ±1° pointing accuracy, and the simulated accuracy of the secondary precise tracking system is 4″, which guaranteed that the coronagraph obtained more than 20,000 images. In subsequent works, we will upgrade and optimize the whole system and conduct our next flight experiment in the future.

Design and implementation of deep learning-based object detection and tracking system

Many human tracking methods by deep learning rely on powerful computing resources. For embedded platforms with limited resources, efficient use of resources is a priority. In this paper, we design an object detection and tracking system based on deep learning methods. We propose an efficient system with software and hardware design. We apply the framework of Vitis AI and its Deep Learning Processing Unit using a hardware/software co-design approach. This approach capitalizes on a higher-level acceleration design framework, where the convolutional models can be updated more flexibly and rapidly. This design approach not only provides a fast design flow but also has good performance in terms of throughput. We facilitate the design and accelerate the object detection model YOLO v3 to achieve higher throughput and energy efficiency. Our tracking method achieves a 1.27x improvement in processing speed with the addition of a single-object tracker. Our proposed human tracking methods can achieve better performance than the others in precision with the same test sequences.

Dual-Axis Solar Tracker

Solar energy is becoming a popular technique to develop sustainable energy sources. Engineering professionals must understand the technologies involved. Solar panel tracking system design and construction are covered in this project. Solar tracking orients the solar array toward the sun, increasing energy output. This system expands on course topics. Solar energy feasibility requires solar array system efficiency optimization. Solar array systems can be improved by sun tracking. This method keeps a solar array facing the sun at all times. Solar modules cleanly turn sunshine into energy in remote areas, solving the power generating problem. The solar tracker designed for this project is reliable and affordable for aligning a solar module with the sun to maximize energy output. Hardware/software hybrid prototype Automatic Sun Tracking System improves solar panel alignment with the sun to maximize energy production and inspire design. Problems and solutions will be discussed.

Solar Panel Sun-Rays Tracking and Cleaning System for Improvement in Power Efficiency

There is an increasing need to reduce greenhouse gas emissions and find more environmentally friendly ways to power the planet. An estimated 4 billion years will pass before the sun stops shining, making it a renewable natural power source. A sustainable method of generating electricity from the sun's energy is offered by solar power systems. In comparison with single axis solar tracker, a dual axis solar tracker tracks the sun at every instance hereby increasing the efficiency by 30-35%. In this system we have a solar panel which tracks the position of the sun and always try to remain perpendicular to sun rays. It will track the sun in all four directions i.e east-west and north-south. This paper focus more on Design of Dual tracking system, which includes installation of GPS and RTC system, stored energy usage for application , periodic cleaning in order to maintain efficiency of panel and comparative analysis of stored energy. Alternative, less expensive options have been suggested because the solar tracking equipment is expensive to manufacture.The goal of this effort is to create a solar dual tracking system model that includes solar panel cleaning as well.

Solar Tracking Methods: A Comprehensive Survey

Abstract: In the pursuit of maximizing solar energy utilization, solar tracking systems have emerged as indispensable tools for enhancing the efficiency of photovoltaic (PV) systems. This comprehensive survey delves into the multifaceted landscape of solar tracking methods, elucidating the diverse techniques and strategies employed in optimizing solar panel orientation relative to the sun's position Solar tracking systems are classified into two primary categories: single-axis and dual-axis tracking. Single-axis tracking systems adjust solar panels along one axis, typically the azimuth axis, while dual-axis tracking systems dynamically alter both azimuth and elevation angles to accurately follow the sun's apparent motion across the sky.Within the realm of solar tracking, passive and active tracking methods are explored. Passive tracking mechanisms rely on natural phenomena such as gravity or thermal expansion to adjust panel orientation, whereas active tracking systems employ mechanical, electrical, or hydraulic actuators driven by motors or other means to actively adjust panel angles based on real-time tracking algorithms.A pivotal aspect of solar tracking systems is the selection and implementation of tracking algorithms. Various algorithms, including sun position algorithms, maximum power point tracking (MPPT) algorithms, and predictive algorithms, are analyzed for their effectiveness in accurately predicting and optimizing solar panel orientation.Furthermore, this survey scrutinizes the role of sensor technologies in solar tracking, encompassing GPS-based tracking, light-intensity-based tracking, weather-based tracking utilizing meteorological sensors, and horizon tracking techniques. These sensor-based methodologies offer different advantages and trade-offs in terms of accuracy, cost, and reliability. To provide a comprehensive understanding, comparative analyses are conducted, evaluating the efficiency, cost-effectiveness, and energy yield of different tracking methods. These comparative assessments offer valuable insights into the performance characteristics and suitability of various tracking methodologies across diverse applications and environmental conditions.In conclusion, this survey serves as an invaluable resource for researchers, engineers, and policymakers involved in the design, development, and optimization of solar tracking systems for renewable energy applications. By synthesizing the latest advancements and comparative analyses, this survey facilitates informed decision-making and fosters the advancement of sustainable solar energy technologies.

Electronic Sunflower Design

Solar energy is known as the most primitive source of energy; it's clean, renewable, abundant, and widely distributed, offering a very broad prospect for utilization. However, the low efficiency of solar energy utilization has always been affecting and hindering the popularization of solar energy technology. The design of a solar tracking system offers a new approach to solving this problem, thereby greatly improving the efficiency of solar energy utilization. This design employs a photoelectric tracking method, using a stepper motor driven by photoelectric sensors, which generate feedback signals to a microprocessor based on the intensity of incident light. The microprocessor runs the program and controls the tracking mechanism to adjust the angle of the solar panels to track the sun. A single-chip microcontroller-implemented solar tracking system can effectively improve the photoelectric conversion efficiency of solar panels and has a broad application prospect.

Fabrication, Design, and Analysis of Dual Axis Solar Tracking System

Energy crisis is one of the prime issues in the third world developing country like Bangladesh. There is an enormous gap between generation and demand of electrical energy. Nearly 50% of the population of the country is extremely isolated from this blessing. Renewable energy is the only answer to solve this issue. Solar energy is one of the most effective resources of renewable energy which could play a significant role in solving this crisis. This research presents a performance analysis of the dual axis solar tracking system using Arduino. The main objective of this research is whether a static solar panel is better than a solar tracker or not. This work is divided into two parts, hardware, and software system. In the hardware part, four light dependent resistors (LDR) is used to detect the utmost light source from the sun. Two servo motors conjointly used to move the solar panel to maximum light source location perceived by the LDRs. In the software part, the code is written by using C programming language and has targeted to the Arduino UNO controller. The outcome of the solar tracker system has analyzed and compared with the fixed or static solar panel found better performance in terms of voltage, current and power. Therefore, the solar tracker has proved more practical for capturing the maximum sunlight supply for star harvesting applications. The result showed dual- axis solar tracking system produced extra 10.53-watt power compared with fixed and single axis solar tracking system. Key Words: Solar Pannel, Servo Motor, LDR

Lyapunov-based control system design for trajectory tracking in electrical autonomous vehicles with in-wheel motors

In this paper, a hierarchical three-layer control structure is presented for the vehicle’s path following. In the first layer, a Lyapunov-based control law is proposed for determining forces and torque required at the vehicle’s center of gravity that guarantees the convergence of tracking errors. Then, a feasible formulation is developed to distribute the longitudinal and lateral forces of the wheels. Each wheel’s forces are distributed in such a way that prevents saturation of that tire. In the third layer, a robust sliding mode control is developed to determine the driving/braking torques of each wheel. Finally, a co-simulation is performed using Carsim and MATLAB/Simulink to evaluate the performance of the proposed control system. The results show that the proposed algorithm is capable of tracking the desired values of the lateral position, velocity, and yaw angle. The Comparison between the proposed control system and two other studies in two different paths including lane-change and two-turn path close to the vehicle’s handling limit is carried out. Our proposed method shows more promising results in terms of root mean square of error criterion than the other two methods. In addition, the proposed controller is able to provide the actuator commands of each wheel properly, despite the parametric uncertainties.

Retraction Notice: Design of Target Detection and Tracking System for Sports Video

Retraction Notice: Design of Target Detection and Tracking System for Sports Video

Dual Axis Solar Tracking System with Weather Monitoring System

This paper presents the design and implementation of a solar tracking system integrated with weather monitoring capabilities. The system is designed to maximize the efficiency of solar panels by continuously adjusting their orientation to track the sun's position throughout the day. In addition to solar tracking, the system incorporates weather monitoring sensors to collect real-time data on environmental conditions such as cloud cover, wind speed, temperature and light intensity. This data is utilized to dynamically adjust the solar panel's position to optimize energy production and system performance in varying weather conditions. The integration of dual-axis tracking with weather monitoring enhances the overall efficiency and reliability of solar energy systems, making them more adaptable to changing environmental factors and increasing their potential for renewable energy generation.