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jaya optimization algorithm implemented on a new novel design of 6-DOF AUV body: a case study

MULTIMEDIA TOOLS AND APPLICATIONS 2022年 1-26页

作者： Basil, Noorulden Marhoon, Hamzah M. M. Gokulakrishnan, S. Buddhi, Dharam Al esraa Univ Coll Dept Comp Tech Engn Baghdad Iraq SKP Engn Coll Dept Math Tiruvannamalai 606611 India Uttaranchal Univ Dharam Buddhi Div Res & Innovat Dehra Dun 248007 Uttarakhand India

The novel jaya optimization algorithm (JOA) was utilized in this research to evaluate the efficiency of a new novel design of Autonomous Underwater Vehicle (AUV). The Three Proportional Integral Derivative (PID) controllers were used to obtain the optimum output for the AUV Trajectory, which can be considered as a main side of the research for solving the AUV Performance. The optimization technique has been developed to solving the motion model of the AUV in order to reduce the rotations of trajectory for the AUV 6-DOF Body in the axis's in x, y and z for the overall positions, velocity were measured in 50 seconds as the velocity compared with the simulated time, and to execute the optimum output for the dynamic kinematics model based on the Novel Euler-6 DOF AUV Body Equation implemented on MATLAB R2021a Version.

关键词： Autonomous underwater vehicle 6-DOF AUV body jaya optimization algorithm Trajectory control PID controller

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Optimal Biped Walking Pattern Generator with Preset Hip-Shift Using jaya optimization algorithm

Optimal Biped Walking Pattern Generator with Preset Hip-Shif...

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International Symposium on Electrical and Electronics Engineering (ISEE)

作者： Tran Thien Huan Ho Pham Huy Anh HCM City Univ Technol & Educ Fac Civil Engn Ho Chi Minh City Vietnam HCM City Univ Technol Fac Elect & Elect Engn Ho Chi Minh City Vietnam

ISBN: (纸本)9781728153537

This paper presents the comparative evolutionary optimization techniques to optimize the design and implementation of the walking pattern generator (WPG) permitting the biped robot able to stably walking with pre-set hip-shift magnitude. The novel jaya optimization algorithm is initiatively applied and comparatively investigated with four different efficient evolutionary optimization techniques including Genetic algorithm (GA), Particle Swarm optimization (PSO), Modified Differential Evolution (MDE), and Central Force optimization (CFO). The comparative performance of five optimization techniques applied on the generic small-sized nonlinear uncertain biped robot (HUBOT-5) comprehensively considered by executing each technique 10 times with the same initial parameters. Using obtained results, it gives the best evolutionary optimization approach for optimize the walking gait generator applied for allowing a stable walking with pre-set hip-shift value. Simulation and experimental results on biped robot HUBOT-5 prove that the jaya optimization algorithm is most feasible.

关键词： Biped robot Walking Pattern Generator (WPG) jaya optimization algorithm Small-sized HUBOT-5 humanoid robot pre-set hip-shift control

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A jaya optimization algorithm Based Unified DPS Control for DAB Based Off-Board EV Chargers

A JAYA Optimization Algorithm Based Unified DPS Control for ...

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Annual Meeting of the IEEE-Industry-Applications-Society (IAS)

作者： Chaurasiya, Saran Singh, Bhim IIT Delhi Dept Elect Engn New Delhi 110016 India

ISBN: (纸本)9781728164014

This paper presents a generalized technique for unique selection of both phase shifts of dual phase shift (DPS) control of DAB. The technique is basically used to minimize the peak current stress while maintaining required amount of power flow with soft switching. For optimizing the current stress at different voltage conversion ratio, multi-objective, multi-constraint jaya algorithm is used. This algorithm basically uses unified current stress as the objective function with mathematical expression of unified power flow is the equality constraint and phase shift boundaries are inequality constraint. This control flow not only provided unique selection criterion for phase shift with minimized current stress but also the phase shift selection considers soft switching performance under all loading conditions. It shows the simulation as well as experimental results on a 1.5 kW designed system. The results are taken with voltage conversion ratio 'K=V-1/NV2' varying from 1 to 0.28 under different loading condition. From obtained results it is shown that when voltage conversion ratio is K=1, then no extra increment in peak of series inductor current. When K=0.28 there is slightly increment in peak of series inductor current. A detailed Simulink control flow model is shown with its closed loop DSP experimental implementation. This model is designed for the control of dual active bridge based off-board charging system.

关键词： DPS control DAB DC-DC Converter EV jaya optimization algorithm Current stress

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DC Motor Speed Control using PID Controller Tuned by jaya optimization algorithm

DC Motor Speed Control using PID Controller Tuned by Jaya Op...

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IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (IEEE ICPCSI)

作者： Achanta, Ravi Kiran Pamula, Vinay Kumar Univ Coll Engn Kakinada Dept ECE JNTUK Kakinada India

ISBN: (纸本)9781538608142

Direct current (DC) motor plays an important role in industries to convert energy from electrical to mechanical. The speed of DC motor is important in the process control industries so we have to control the speed of DC motor. For this speed control proportional-integral-derivative (PID) controllers are used. For better performance and optimum parameters, PID tuning is used. Traditional tuning techniques for classical PID controller suffer from many disadvantages like non-customized performance measure and insufficient process information. In this paper, we use the jaya optimization algorithm (JOA) for better performance in speed control and time response of the system. Experimental results are presented to study the performance of JOA based PID controller in comparison with particle swarm optimization (PSO) based PID controller. Practical validation is done on QNET 2.0 DC motor by using LabVIEW (R) software.

关键词： DC motor jaya optimization algorithm Particle swarm optimization PID controller

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Android ransomware detection using binary jaya optimization algorithm

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EXPERT SYSTEMS 2024年第1期41卷 e13479-e13479页

作者： Alazab, Moutaz Al Balqa Appl Univ Fac Artificial Intelligence Al Salt Jordan Al Balqa Appl Univ Dept Intelligent Syst Al Salt 19385 Jordan

Ransomware is a serious security concern to mobile devices, as it prevents the use of the device and its contents until a ransom is paid, resulting in considerable financial losses for both people and corporations. The existing anti-malware measures have shown to be inadequate in combatting new malware variants that utilize advanced evasion strategies like Polymorphic, Metamorphic, Dynamic Code Loading, Time-based evasion, and Reflection. Furthermore, these primary defences have also suffered from low detection rates, significant false positives, high processing times, and excessive processing and power consumption that is inappropriate for smartphones. This paper offers the binary jaya (Bjaya) for ransomware detection in Android mobile devices using the Bjaya optimization-based algorithm. The developed algorithm's effectiveness has been assessed against two datasets, the 0-1 knapsack, and real ransomware dataset. The proposed Bjaya method surpassed the other algorithms on 85% of the 0-1 knapsack datasets. The suggested Bjaya method was also tested on a ransomware dataset in two phases. In the first stage of testing, Bjaya outperformed other standard classifiers with sensitivity and Gmean values of 97% and 98.2%, respectively. In the second stage of testing, Bjaya outperformed other GA, FPA, and PSO metaheuristic algorithms in terms of specificity, sensitivity, and Gmean. These findings indicate the applicability of the suggested Bjaya algorithm for ransomware detection.

关键词： 0-1 knapsack problem Android intelligent methods jaya optimization algorithm machine learning ransomware detection

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A Novel Hybrid Fuzzy-jaya optimization algorithm for Efficient ORPD Solution

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IEEE ACCESS 2019年 7卷 182078-182088页

作者： Gafar, Mona G. El-Sehiemy, Ragab A. Hasanien, Hany M. Prince Sattam Bin Abdulaziz Univ Coll Sci & Humanities Al Sulail Dept Comp Sci Kharj 16278 Saudi Arabia Kafrelsheikh Univ Fac Artificial Intelligence Machine Learning & Informat Retrieval Dept Kafr El Shaikh 33516 Egypt Kafrelsheikh Univ Fac Engn Elect Engn Dept Kafr El Shaikh 33516 Egypt Future Univ Egypt Fac Engn & Technol Elect Engn Dept Cairo Egypt

This paper is concerned with the application of hybrid fuzzy-jaya optimization algorithm to find the solution of non-linear optimal reactive power dispatch (ORPD) problem in power systems. The proposed hybrid optimization algorithm combines the merits of fuzzy principle and the jaya optimizer. Fuzzification of the ORPD variables is employed by pseudo goal strategy. Two technical objectives are minimized individually and simultaneously to enhance the overall power systems performance. These objectives are transmission active power losses and voltage deviation at load buses. The ORPD objectives are optimized considering both inequality and equality constraints that reflect the operation needs. The hybrid fuzzy-jaya is established as efficient optimization method that is achieving the global optimal solution. The effectiveness of the proposed hybrid algorithm for solving the ORPD problem is proven by using three standard IEEE test networks. An assessment of the proposed hybrid algorithm is carried out compared with other optimization algorithms those reported in the literature. The simulation results assure that the fuzzy jaya hybrid algorithm leads to significant power system performance enhancement for different scale power systems.

关键词： Fuzzy logic jaya optimization algorithm hybrid strategy ORPD pseudo goal strategy minimization of transmission power losses enhancement of load buses voltage profile

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Adaptive WADC scheme for damping inter-area oscillation based on jaya optimization algorithm in the presence of variable time latencies from WAMS data

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INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2021年第12期31卷

作者： Goudarzi, Hossein G. Yousefi, Borzou Rezvani, Mohammad Shirazi, Abdolreza N. Islamic Azad Univ Nour Branch Dept Elect Engn Nour Iran

The continual increase in the power network topological structure and long distances between load-generation sources lead to modern powers systems are operated near theirs stability margins. For this issue, reliable and secure operations of electric devices through inter-area oscillations remain an essential issue in the system dynamic stability. In the case of improper actions of controlling devices, the severe inter-area interactions may lead to wide-area instabilities and large blackouts. Using wide-area measurement system (WAMS), remote signals are transferred through communications links with different inherent time latencies. In the case of large time delays, the main controllers cannot work appropriately which leads to improper performance of damping controllers through severe inter-area fault event scenarios. For this issue, this paper presents an adaptive wide-area damping controller (AWADC) for damping inter-area oscillations in large power systems equipped with WAMS technology consisting of various time latencies. In this case, based on the IEEE C37.118.1 protocol, the generator buses are equipped with phasor measurement unit devices. Also, owing to the different communication links, the measured global signals (GSs) are involved within different time latencies. In this case, at each time window, considering time delay compensator (TDC) technology provided through Simevents discrete event tool, the overall time delay is evaluated and compensated. For identifying the best controlling GSs, considering two observability and controllability concepts, the system dynamic signals are evaluated which the best input decisioning signals and corresponding output controlling signals are provided. The proposed AWADC scheme consists of different compensating blocks which are adjusted through simple and well-known jaya optimization algorithm (JOA) through online evaluations. The structure of the proposed AWADC controlling scheme is carried out on a modified 39-bus New E

关键词： adaptive wide area damping controller inter-area oscillation jaya optimization algorithm time latency compensator wide-area measuring system

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Proximity-Distance Mapping and jaya optimization algorithm Based on Localization for Wireless Sensor Network

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2022年第6期36卷

作者： Peng, Duo Gao, Yuwei Lanzhou Univ Technol Sch Comp & Commun Lanzhou 730050 Peoples R China

Aiming at the problem of large location errors of traditional ranging-free algorithms in Wireless Sensor Network (WSN), a novel node location algorithm based on proximity-distance mapping (PDM) and jaya optimization was proposed. In this algorithm, proximity and Euclidean distance are extracted from the relationship of anchor nodes to construct a mapping matrix by using the idea of PDM. It is calculated by using the mapping matrix that the estimated distance from the unknown node to the anchor node can be used for the subsequent calculations. After the estimated distance is obtained, the jaya optimization algorithm is imported to calculate the location of the unknown one. To accelerate the convergence and enhance the accuracy of the algorithm, the idea of a boundary box is used to limit the initial feasible region of unknown nodes. The experiment results show that the PDM-jaya algorithm has better positioning accuracy than the original PDM in the same condition.

关键词： Wireless sensor network localization algorithm jaya optimization algorithm proximity-distance mapping

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Optimal nature-walking gait for humanoid robot using jaya optimization algorithm

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ADVANCES IN MECHANICAL ENGINEERING 2019年第11期11卷

作者： Tran Thien Huan Ho Pham Huy Anh Cao Van Kien HCM City Univ Technol & Educ HCM UTE Fac Civil Engn Dept Mech Ho Chi Minh City Vietnam HCM City Univ Technol Vietnam Natl Univ Ho Chi Minh City VNU HCM Fac Elect & Elect Engn Ho Chi Minh City 70000 Vietnam

This article proposes a new method used to optimize the design process of nature-walking gait generator that permits biped robot to stably and naturally walk with preset foot-lift magnitude. The new jaya optimization algorithm is innovatively applied to optimize the biped gait four key parameters initiatively applied to ensure the uncertain nonlinear humanoid robot walks robustly and steadily. The efficiency of the proposed jaya-based identification approach is compared with the central force optimization and improved differential evolution (modified differential evolution) algorithms. The simulation and experimental results tested on the original small-sized biped robot HUBOT-4 convincingly demonstrate that the novel proposed algorithm offers an efficient and stable gait for humanoid robots with precise height of foot-lift value.

关键词： Uncertain nonlinear humanoid robot jaya optimization algorithm central force optimization algorithm modified differential evolution algorithm nature-walking gait generator gait optimization for humanoid robot zero-moment point concept inverse and forward kinematics

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Safeguarding IoT consumer devices: Deep learning with TinyML driven real-time anomaly detection for predictive maintenance

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AIN SHAMS ENGINEERING JOURNAL 2025年第2期16卷

作者： Katib, Iyad Albassam, Emad Sharaf, Sanaa A. Ragab, Mahmoud King Abdulaziz Univ Fac Comp & Informat Technol Jeddah 21589 Saudi Arabia

Internet of Things (IoT) security is paramount for enterprises, as it includes several strategies, techniques, actions, and protocols that aim to alleviate the high vulnerability of cutting-edge businesses. IoT consumer devices, from smart home appliances to wearable gadgets, have become ubiquitous daily, facilitating automation and seamless connectivity. However, ensuring their reliability and security presents a tremendous challenge. Anomaly detection methods offer a promising solution, especially those powered by TinyML (Machine Learning (ML) on Tiny Devices). These IoT devices can autonomously identify unusual behaviours or patterns that diverge from regular operation by leveraging the proficiencies of deep learning (DL) techniques enhanced for resource- constraint environments, like neural networks. Incorporating DL, anomaly detection, and TinyML allows realtime monitoring and proactive mitigation of malfunctions or security breaches in IoT devices. This advanced technology ensures improved reliability, privacy, and overall user experience in the dynamic landscape of connected devices, whether identifying irregular health data or detecting unauthorized access attempts on a smart door lock from the wearable fitness tracker. Therefore, this study develops a new Deep Learning technique to secure IoT consumer devices with TinyML Driven Real-time Anomaly Detection for Predictive Maintenance (DLTML-RTADPM). The DLTML-RTADPM technique aims to recognize and categorize the anomalies in IoT consumer devices. At the primary phase, the DLTML-RTADPM model normalizes the input data using Z-score normalization. In the DLTML-RTADPM method, the Fennec Fox optimization algorithm (FFA) is used for a high dimensionality reduction process where the optimal feature set is chosen. The DLTML-RTADPM technique implements gradient least mean squares with a bidirectional long short-term memory (GLMS-BiLSTM) approach for anomaly detection. To further improve the detection results of the DL

关键词： Internet of things Anomaly detection TinyML jaya optimization algorithm Deep learning Feature selection

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