IAES International Journal of Robotics and Automation (IJRA)
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Development of an Arduino-based field heat regulator for fruit storage and transportation
Get PDFFruit spoilage during transportation is a major problem that results in significant economic losses for fruit producers and distributors. One of the primary causes of fruit spoilage is heat buildup inside the storage container during transportation. Hence, this study was done to design and develop an Arduino-based field heat regulator for fruit storage and transportation, regulate field heat in terms of temperature and humidity monitoring; and assess its influence in terms of the skin color, firmness, and bruising of the fruit specimen. After the conduct of the study, it was found that the regulator underwent several iterations during product development and was tried out in an actual transportation procedure. The results revealed that during transportation the product was subjected to fluctuations in temperature and relative humidity, but the storage regulated heat by maintaining desired conditions. Additionally, there was a significant difference found in terms of the fruit's quality parameters when transported using the proposed storage and the traditional method. In conclusion, this storage has the potential to be used in fruit storage facilities, helping reduce post-harvest losses and decrease the chances of fruits being spoiled easily
Theoretical and experimental analysis of unbalanced doubly fed induction generators
Get PDFIn this paper, a novel approach has been developed for the modeling and analysis of doubly fed induction generators operating under unbalanced load conditions. This comprehensive approach considers the derivation of the doubly fed induction generator’s neutral voltage during unbalanced conditions. Using this innovative approach, important and extremely precise signatures on stator currents and voltages have been extracted during a rational simulation time. It has been shown that for unbalanced conditions, an abnormal operation is produced. It is characterized by unbalanced stator voltages, currents, and specific harmonics through the stator variables. These harmonics have been proposed to detect unbalanced conditions. The consistency and reliability of this approach for the analysis and modeling of unbalanced doubly fed induction generators are validated by the coherence and good correlation between experimental and simulation results
Development of an unmanned ground vehicle for seed planting
Get PDFAs global population growth intensifies the demand for sustainable food production, the application of robotics to agriculture emerges as a promising solution. This research focuses on the design, development, and deployment of an unmanned ground vehicle for seed planting, also known as a robotic seed planter. The robotic seed planter automates seed planting processes, offering advantages such as increased accuracy, reduced labour requirements, and optimal resource usage. Parametric Technology Corporation (PTC) Creo was used for the structural design, Proteus 8.14 for the circuitry design, and Arduino IDE 2.0 with Visual Studio Code for the programming. The design incorporates seed metering and drilling mechanisms guided by intelligent systems. Results show exceptional accuracy in seed placement (94%), operational efficiency, and adaptability to diverse conditions, with energy consumption relatively low. The planter is equipped with a web application for remote monitoring and control. The application is hosted on one of the microcontrollers and WebSockets protocol is utilized for inter-microcontroller communication. It offers an auto mode for automated planting and Manual mode for easier manoeuvrability. The findings of this study demonstrate the robotic seed planter’s transformative impact on precision agriculture, providing a glimpse into the future of efficient and sustainable farming operations
Design and development of a quadruped home surveillance robot
Get PDFQuadruped home surveillance robots represent a promising advancement in home security and automation. This innovative robotic system is equipped with four-legged locomotion, allowing it to traverse various terrains within a household environment. The robot's primary function is surveillance, and it is equipped with high-definition cameras, motion sensors, and object recognition software. These sensors enable the robot to detect intruders, track their movements, and capture real-time video footage for remote monitoring. The quadruped robot's compact and agile design allows it to navigate through narrow spaces and overcome obstacles, ensuring it can patrol every corner of a home effectively. Its autonomous operation is made possible through advanced artificial intelligence algorithms, ensuring that it can detect anomalies and respond to security threats promptly. Furthermore, integrating the robot with smart home systems enables seamless communication with other connected devices and allows homeowners to control and monitor it remotely
Analysis of inertia, damping, and synchronization characteristics in grid-connected photovoltaic systems with fuzzy logic control
Get PDFThe integration of renewable energy sources (RES) into DC-distributed power systems (DC-DPSS) is gaining traction as a sustainable energy solution. However, the inherent variability of RES output can introduce instability into the grid, posing challenges for maintaining system reliability and stability. Fuzzy logic controllers (FLCs) have emerged as a promising approach to mitigate these instability issues, offering a robust and adaptable control strategy that can effectively handle the complexities of DC-DPSS. This paper examines the application of FLCs in DC-DPSS, exploring their effectiveness in addressing instability caused by RES fluctuations. FLCs are a control system that leverages fuzzy logic, a form of logic that utilizes linguistic variables to represent uncertainty, make decisions, and improve the stability of DC-distributed power systems. The research analyzes various system parameters, including inertia, damping, and synchronization characteristics, using a static synchronous generator (SSG) model. The study builds upon prior findings by adding a fuzzy logic controller to the existing system. The results showed better performance which resulted in improved inertia, damping, and synchronization characteristics. The efficiency of the proposed controller is demonstrated using MATLAB/Simulink
Vector synthesis of fault testing map for logic
Get PDFVector synthesis of fault testing (simulation) map for logic is proposed, which without simulation allows to determine of all faults detected on test sets, as well as determining test sets to detect specified faults. For synthesis, a superposition of smart data structures is used, containing: a deductive matrix D, as a derivative of the logical vector L, test truth table T, and fault truth table F. The deductive matrix is seen as the gene of functionality and base of fault simulation mechanism to solve all the problems of testing and verification. In the matrix synthesis, an axiom is used: all the mentioned tables are identical in shape to each other and always interact with each other convolutionally T⊕L⊕F=0. A universal deductive reversing converter “test-faults” and “faults-test” for logical functionalities of any dimension is proposed. Converter functions: fault simulation on test sets T→F and synthesis of test sets F→T to detect the specified faults. The converter can be used as a test generation and fault simulation service for IP-core system-on-chip (SoC) under the IEEE 1500 SECT standard. Based on the deductive matrix, a fault testing map for logic is built, where each test set is matched with the logic-detected faults of the input lines
Design and implementation of deep neural network hardware chip and its performance analysis
Get PDFThe artificial neural network (ANN) with a single layer has a limited capacity to process data. Multiple neurons are connected in the human brain, and the actual capacity of the brain lies in the interconnectedness of multiple neurons. As a specified generalization of ANN deep learning makes use of two or more hidden layers, which implies that a greater number of neurons are required to construct the model. A network that has more than one hidden layer, also known as two or more hidden layers, is referred to as a deep neural network, and the process of training such networks is referred to as deep learning. The research article focuses on the design of a multilayer or deep neural network presented for the target field programmable gate array (FPGA) device spartan-6 (xc6stx4-2t9g144) FPGA. The simulation is carried out using Xilinx ISE and ModelSim software. There are two hidden layers in which (2×1) multiplexer blocks are utilized for processing twenty neurons into the output of ten neurons in the first hidden layer and demultiplexers (1×2) and vice versa. The hardware utilization is estimated on FPGA to compute the performance of the deep neural hardware chip based on memory, flip flops, delay, and frequency parameters. The design is scalable and applicable to various FPGA devices, which makes the work novel. FPGA-based neuromorphic hardware acceleration platform with high speed and low power for discrete spike processing on hardware with great real-time performance
Nonlinear Kalman filter for gyroscopic and accelerometer noise rejection of an unmanned aerial vehicle control strategy
Get PDFThis study addresses timing issues inherent in traditional proportional-integral-derivative (PID) controllers for drone angle control and introduces an innovative solution, the adaptive PID flight controller, aimed at optimizing PID gains for improved performance in terms of speed, accuracy, and stability. To enhance the controller's robustness against noise and accurately estimate the system's state, a Kalman filter is incorporated. This filtering mechanism is designed to reject noise and provide precise state estimation, thereby contributing to the overall effectiveness of the adaptive PID flight controller in managing altitude dynamics for unmanned aerial vehicles (UAVs). The comparative methodology evaluates three configurations: a single PID controller for all three angles, two PID controllers dedicated to pitch/roll and yaw angles separately, and three PID sub-controllers for each angle (pitch, roll, and yaw). The study seeks to identify the most effective PID configuration in terms of stability, responsiveness, and accuracy while highlighting the added benefits of noise rejection and state estimation through the Kalman filter. This integrated approach showcases innovation and effectiveness, introducing a comprehensive solution not explored in previous research
Wireless sensor networks protocols, applications, and network-on-chip communications
Get PDFA wireless sensor network (WSN) is a network consisting of self-governing sensors that are deployed in space and communicate with each other using wireless technology to monitor physical or environmental variables. These networks generally include compact, inexpensive sensor nodes equipped with sensing, processing, and communication functionalities. WSNs are specifically engineered to gather data from their immediate environment, do local data processing, and subsequently communicate pertinent information either to a central hub or to other interconnected nodes within the network. Continuous research in the domain of WSNs is devoted to advancing security concerns, developing novel sensing technologies, and optimizing communication protocols. The advancements in these domains enhance the ongoing development and efficiency of WSNs. The WSNs are very important for getting information from the real world in many situations. WSNs are flexible tools for keeping an eye on and controlling different environments because they have sensor nodes, wireless communication, and distributed processing. WSNs use network-on-chip (NoC) communication architecture to connect sensor nodes. The article explains the introduction to WSN, the background of wireless communication, motivation, ZigBee protocol, and WSN applications
Inverse kinematics of six degrees of freedom robot manipulator based on improved dung beetle optimizer algorithm
Get PDFInverse kinematics is a basic problem in robotics, which aims to solve the robot’s joint angles according to the end effector’s position and orientation. This paper proposed an improved spiral search multi-strategy dung beetle optimizer (DBO) algorithm for solving the inverse kinematics problem. The improved DBO algorithm considers not only the error between the target value and the current value but also the previous position of the robot to ensure minimum displacement during the movement. To solve the end position error and orientation error of the robot end effector more accurately, the quaternion is introduced as a penalty factor in the optimization objective function, which is of great significance for reducing the orientation error. Through the improved DBO algorithm, the position error is still accurate, and the orientation error is reduced from 9.5901 to 1.8718. Experimental results show that the proposed algorithm outperforms other swarm-intelligent algorithms in terms of accuracy and convergence speed. Overall, the proposed spiral search multi-strategy DBO algorithm provides an effective and efficient solution to the inverse kinematics problem in robotics