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A superior secure key spawn using boosted uniqueness encryption for cloud computing in advanced extensive mobile network Chandra, G. Rajesh; Mohan, K. Jagan; Khalaf, Osamah Ibrahim; Gopisetty, Guru Kesava Dasu; Anand, Dama; Algburi, Sameer; Lakshmi, S. Vijaya
SINERGI Vol 28, No 2 (2024)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2024.2.019

The cloud computing sector, including mobile networks has increased in the present time. Because of advanced features and security related information in cloud. So many methods are available for handling these problems. Cloud security, large number of methods existing for provide security. Among that, so many widespread techniques cast-off to protected data in cloud based on Individuality based encryption. This method specialty is allowing only authorized end users for access legal data and avoid smalevolent attack. Individuality -based encryption method follows up the four stages like Name, Key generation, encryption and decryption. Among these Key generation is most important for generating secure key. It provides unbreakable and non-derivable secure keys to provide strong security. This paper provides a novel approach for providing advanced security called identity-based encryption. This approach uses segment of a bitidentity thread in demandto evade seepage of user’s data identity, if any attacker decodes the key also. Statistical reports show that the proposed algorithm takes less time in the process of decryption and encryption compared to other traditional approaches. One more feature of our novel method is skinning the user’s uniqueness by using parametric curve fitting. It contains a polynomial interpolation function.

Design and Analysis of a Hybrid Intelligent SCARA Robot Controller Based on a Virtual Reality Model Al Mashhadany, Yousif; Abbas, Ahmed K.; Algburi, Sameer; Taha, Bakr Ahmed
Journal of Robotics and Control (JRC) Vol 5, No 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23158

SCARA robots have been used in various fields of robotics, such as biomedical engineering, automation, industrial, and gaming. However, our SCARA (Selective Compliance Assembly Robot Arm) VR model stands out with its realistic design and construction assumptions. The VR testing of the robot's motion envelope has facilitated a more precise inverse kinematics solution and verification of the dynamic process. The intelligent controller of this application, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique and a classical proportional-integral-derivative (PID) controller, offers an optimized solution to the accuracy problem. The hybrid ANFIS controller starts with the PID setting parameters of the resultant solution. Following thorough testing of the suggested SCARA manipulator with an intelligent controller in a virtual reality environment, researchers recognized the physical system's potential for implementation utilizing multiple control approaches. Despite the intricacy of its design and implementation, the intelligent controller's software ensures that the system runs at top efficiency. This application replicates the user interface of the MATLAB/SIMULINK var (2022b), which produced promising robotics results, demonstrating its trustworthiness as a realistic, intelligent model, and virtual reality was critical in the development of the SCARA manipulator. It digs into the design and analysis of a hybrid intelligent controller for SCARA robots, which are widely used in assembly lines and manufacturing. Finally, the proposed controller combines the best features of an Adaptive Neuro-Fuzzy Inference System (ANFIS) with a conventional proportional-integral-derivative (PID) controller to resolve application accuracy difficulties as efficiently as possible.

Design and Analysis of a Hybrid Intelligent SCARA Robot Controller Based on a Virtual Reality Model Al Mashhadany, Yousif; Abbas, Ahmed K.; Algburi, Sameer; Taha, Bakr Ahmed
Journal of Robotics and Control (JRC) Vol. 5 No. 6 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i6.23158

SCARA robots have been used in various fields of robotics, such as biomedical engineering, automation, industrial, and gaming. However, our SCARA (Selective Compliance Assembly Robot Arm) VR model stands out with its realistic design and construction assumptions. The VR testing of the robot's motion envelope has facilitated a more precise inverse kinematics solution and verification of the dynamic process. The intelligent controller of this application, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) technique and a classical proportional-integral-derivative (PID) controller, offers an optimized solution to the accuracy problem. The hybrid ANFIS controller starts with the PID setting parameters of the resultant solution. Following thorough testing of the suggested SCARA manipulator with an intelligent controller in a virtual reality environment, researchers recognized the physical system's potential for implementation utilizing multiple control approaches. Despite the intricacy of its design and implementation, the intelligent controller's software ensures that the system runs at top efficiency. This application replicates the user interface of the MATLAB/SIMULINK var (2022b), which produced promising robotics results, demonstrating its trustworthiness as a realistic, intelligent model, and virtual reality was critical in the development of the SCARA manipulator. It digs into the design and analysis of a hybrid intelligent controller for SCARA robots, which are widely used in assembly lines and manufacturing. Finally, the proposed controller combines the best features of an Adaptive Neuro-Fuzzy Inference System (ANFIS) with a conventional proportional-integral-derivative (PID) controller to resolve application accuracy difficulties as efficiently as possible.

Robust Power Management for Smart Microgrid Based on an Intelligent Controller Alsanad, Hamid R.; Al Mashhadany, Yousif; Algburi, Sameer; Abbas, Ahmed K.; Al Smadi, Takialddin
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.23554

A microgrid (MG) is an autonomous electrical system that can operate independently or link to the grid. It is usual practice to use a single grid organization to improve energy access and ensure a consistent supply of electricity. Microgrids (MGs) can be unstable if islanded given that they lack the predominant grid's high friction and are subject to large voltage and frequency swings. Standards, directions, and accessibility and interoperability criteria all address the dependability of a microgrid, the use of distributed local resources, and cybersecurity. This work presents a revolutionary intelligent controller, Adaptive. This study proposes a novel intelligent controller, the Adaptive Network-based Fuzzier Inference System - Drooping Controller (ANFISDC), with a drooping coefficient modification, to provide optimal power sharing while minimizing power overloading/curtailment. To provide the essential stability and lucrative power sharing for the islanded the microgrid, the dropping coefficient is changed to account for the power fluctuations of RES (renewable energy source) components as well as the relationship between electricity production and demand. Furthermore, secondary control is used to restore the frequency/voltage drop caused by the droop control. Simulations with load fluctuations in MATLAB/Simulink show that the proposed strategy improves the stability and economic viability of microgrids powered by energy from renewable sources based on droop. The outcomes of the simulation demonstrate how well the suggested ANFISDC approach works to keep the microgrid operating steadily and profitably.

Optimal Mobile Robot Navigation for Obstacle Avoidance Based on ANFIS Controller Saleh, Mohamed S.; Al Mashhadany, Yousif Ismail; Alshaibi, Maather; Ameen, Ferdous Majeed; Algburi, Sameer
Journal of Robotics and Control (JRC) Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v6i1.24882

Over the past 20 years, there has been a lot of research done on the movement control issue of an automated wheeled movable robot. This paper suggests navigation and collision avoidance in a new setting by utilizing the sensor-based steering angle control method, the Adaptive Neuro-Fuzzy Inference System (ANFIS) controller has already been introduced for the safety of navigation of single and multiple movable robots in cluttered surrounding areas. The front, right, and left obstruction distances have been measured using the sharp infrared reported significant and the ultrasonic distance finder sensor. This paper proposes navigating and collision avoidance in a unique environment. It uses the sensor-based angle of steering control approach. The acute ultraviolet detected is significant, and an ultrasound distance finder sensor was utilized to determine front, right, and left jump distances. In this study, a multi-layer ANFIS controller is used, with two levels for movement and the others for hurdle avoidance. The proposed ANFIS controller must be tested using a Matlab simulation. In six separate test situations, six obstacles in the surrounding region are used in a simulation, and then the robot can reach the objective without collisions in the shortest course.

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