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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.

Design and Hardware Implementation of Combining PD with HSSC for Optimizing Behavior of Magnetic Levitation System Alrawi, Ali Amer Ahmed; Lilo, Moneer Ali; Al Mashhadany, Yousif
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.v6i1.23940

This paper presents the design and implementation of a hybrid control system that uses Proportional-Derivative (PD) and High-Speed Switching Controller (HSSC) methods to enhance Maglev system performance. The goal is to design controllers that properly follow input references and improve system stability and reactivity. The PD controller is fast and easy to install, but it cannot handle system disturbances and nonlinearities, which might cause instability. HSSC integration addresses these issues. The HSSC makes the PD controller more resilient to external forces and nonlinear dynamics. The combined PD-HSSC approach ensures stable levitation, precise positioning control, and system reliability in various conditions. The hybrid system reduced steady-state error and maintained system stability under dynamic input conditions, although it over-shoot more than PD alone. The computer-aided real time simulation of system dynamics is done, and the control rules are formulated out of a combination of PD Control for normal control processes and the HSSC for enhanced robustness. The total control current is given by the algebraic addition of the PD control action going, the equivalent control going, and the switching control going. However, the proposed PD-HSSC technology is possible to provide a stable levitation state for the control of precise position, even in the nonlinear and disturbance conditions The experimental results showed an 89% enhancement in the efficiency of the hybrid control system. The integration of PID (Proportional-Integral-Derivative) and HSSC has been developed in this system using MATLAB Simulink. The real-time findings demonstrate that the PD-HSSC system is higher in stability for operating the maglev system. This is due to its much lower steady-state error compared to the PD system, regardless of the kind of step input or dynamically fluctuating sine and square wave inputs. However, PID_HSSC exhibited a greater degree of overshoot in comparison to the PD.

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