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INDONESIA
Mechatronics, Electrical Power, and Vehicular Technology
Published by Lembaga Ilmu Pengetahuan Indonesia
ISSN : 20873379     EISSN : 20886985     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Mechatronics, Electrical Power, and Vehicular Technology (hence MEV) is a journal aims to be a leading peer-reviewed platform and an authoritative source of information. We publish original research papers, review articles and case studies focused on mechatronics, electrical power, and vehicular technology as well as related topics. All papers are peer-reviewed by at least two referees. MEV is published and imprinted by Research Center for Electrical Power and Mechatronics - Indonesian Institute of Sciences and managed to be issued twice in every volume. For every edition, the online edition is published earlier than the print edition.
Arjuna Subject : -
Articles 631 Documents
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Voice command classification for mobile robotic control using mel frequency cepstral coefficients and support vector machines Ratna Hartayu; Santoso Santoso; Ahmad Ridho’i; Ayusta Lukita Wardani; Yunus Awwalu Romadhon
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1373

Abstract

Voice command recognition plays a crucial role in enabling intuitive interaction in robotic and embedded control systems. This study proposes a voice command classification system based on Mel-frequency cepstral coefficients (MFCC) and support vector machine (SVM) using the Google speech commands dataset v2. Eight command classes (“down”, “go”, “left”, “no”, “right”, “stop”, “up”, and “yes”) were used. The dataset was divided into 80 % training and 20 % testing sets, with hyperparameter tuning performed using 5-fold cross-validation on the training data. MFCC feature extraction employed 13 static coefficients augmented with delta and delta-delta features, resulting in a 39-dimensional frame-level representation and a 78-dimensional utterance-level feature vector. Experimental results show that the SVM with radial basis function (RBF) kernel achieved optimal performance with parameters C = 100 and γ = 0.01, yielding 96.2 % accuracy, 96.5 % precision, 96.0 % recall, and 96.2 % F1 score. The inclusion of dynamic features improved accuracy by 4.7 % compared to static MFCCs. The system demonstrates a lightweight architecture suitable for low-resource environments; however, experiments were primarily conducted under clean conditions, and robustness evaluation was limited to a single noise level (20 dB SNR). Furthermore, real-time deployment on embedded hardware was not experimentally validated and remains part of future work.
Analytical optimization of displacer trajectory for ideal beta-type stirling engine cycles with sinusoidal piston motion Rachman Hakim; Toto Hardianto; Priyono Sutikno; Poetro Sambegoro
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1486

Abstract

This study develops a generalized displacer motion equation for a beta-type Stirling engine. The proposed equation approximates the ideal Stirling cycle while maintaining sinusoidal piston motion to ensure stable power extraction. The displacer trajectory is modeled with a Fourier series and optimized. The resulting trajectory is then generalized as a piecewise function to improve applicability across different geometries. This approach improves control of working fluid distribution, allowing the expansion and compression processes to more closely approach isothermal conditions. The results show that the optimized Fourier trajectory achieves 91.9 % of the ideal Stirling-cycle work output, outperforming conventional drive mechanisms, where it only achieves 59.8 % for crank mechanism, 66 % for Scotch yoke, and 68.5 % for rhombic drive. For practical implementation, the optimized Fourier trajectory is generalized using a piecewise formulation. The generalized trajectory maintains approximately 80–90 % of the ideal Stirling-cycle work over a range of compression ratios without requiring re-optimization. These results demonstrate that the proposed approach provides both high thermodynamic performance and improved adaptability compared with conventional Stirling engine drive mechanisms.
Adaptive PID control using TSK elliptic fuzzy and static feedforward for observable disturbance rejection in industrial heating ovens Ali Rospawan; Clara Lavita Angelina; I Made Andik Setiawan; Zanu Saputra; Ocsirendi Ocsirendi; Aan Febriansyah; Indra Dwisaputra; Dedy Ramdhani Harahap
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1094

Abstract

This paper presents an advanced control strategy aimed at accelerating the temperature recovery time in industrial heating ovens, particularly in response to observable disturbances such as periodic door openings. The proposed method combines a Takagi-Sugeno-Kang (TSK) elliptic fuzzy-based adaptive proportional-integral-derivative (PID) control with a static feedforward (FF) control strategy. The TSK elliptic fuzzy system models the input-output dynamics and adaptively adjusts the PID gains, allowing the controller to respond effectively to varying system conditions. The static feedforward control is designed to specifically counteract the measurable disturbances to shorten recovery time and improve stability. The strategy is validated through both simulation and experiment on a low-cost STM32 microcontroller. Compared with a conventional PID controller, it reduced the RMSE by 32.27 % and the ISE by 54.13 %, together with a recovery time shortened by approximately 72 s, reflecting the faster disturbance recovery achieved by the static feedforward action. Experimental results confirmed these findings, with a higher feedforward gain further reducing the temperature drop and accelerating recovery. The proposed technique offers a reliable and practical solution for practitioners in managing similar disturbance patterns in industrial settings.
Multi-LiDAR SLAM and intelligent navigation for autonomous logistic robots in ROS2 environments Leonard Priyatna Rusli; Michael Jonathan; Rusman Rusyadi
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1187

Abstract

Traditional automated guided vehicles (AGVs) are restricted by their reliance on predefined paths, limiting adaptability in dynamic warehouse environments. While autonomous mobile robots (AMRs) overcome this limitation through on-board simultaneous localization and mapping (SLAM) and autonomous navigation, standard configurations often suffer from top mounted-sensor blind spots when loads are carried on the chassis. To address these coverage gaps, an indoor logistic AMR based on the robot operating system 2 (ROS2) was designed and evaluated. The platform was developed by combining a multi-LiDAR perception stack with low-cost industrial actuation and a lightweight, fleet-style user interface. Within the system architecture, data from two light detection and ranging (LiDAR) sensors were merged at the topic level into a single virtual scan for SLAM toolbox and Nav2. Additionally, actuation and wheel odometry were driven by an RS-485 Modbus-based brushless DC (BLDC) motor controller, while ultrasonic sensors for short-range safety, an inertial measurement unit (IMU) for orientation, and a network of microcontroller calling stations communicating via message queuing telemetry transport (MQTT) were integrated into the platform. Experimental validation demonstrated successful multi-LiDAR fusion, with the Modbus motor driver achieving a motion-control error of 0.36 % and a speed-retrieval error of 0.43 %. Furthermore, calling-station commands were reliably executed over MQTT, and a point-to-point navigational repeatability of 10.3 cm was achieved. These findings indicate that an integrated multi-LiDAR ROS2 AMR provides a highly practical solution for indoor logistics. Through the proposed sensor merger and calling-station handshake, two recurring vulnerabilities of standard ROS2 deployments—single-LiDAR coverage gaps and Nav2 goal-overwriting behavior—were successfully resolved.
Front Cover MEV Vol 17 Iss 1 Yanuandri Putrasari
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

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Abstract

Development of a human wrist joint rehabilitation robot with AFC-PID control Abbas Moloody; Mohammad Mahjoob; Azizan As’arry; Mohd Zarhamdy Mohd Zain
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1249

Abstract

Robotics is transforming healthcare rehabilitation by improving precision, efficiency, and accessibility. While industrial robots are widely used, service robots in medical applications remain underutilized. Wrist rehabilitation is essential for restoring mobility and strength after injury or surgery. This study presents a three degrees of freedom (DOF) robotic system designed to assist patients with wrist mobility impairments, aiming to enhance rehabilitation outcomes. This study develops a 3-DOF wrist rehabilitation robot with active force control – proportional-integral-derivative (AFC-PID) control to enhance rehabilitation outcomes. Traditional rehabilitation methods for wrist impairments are time-consuming, physically demanding, and inconsistent. Patients require structured therapy to reduce stiffness, receive corrective assistance for incomplete movements, and strengthen muscles. The limitations of conventional treatments create a need for more efficient and accessible therapeutic solutions. The robotic system operates in three phases: phase 1 (passive mode) where the robot aids wrist movement to relax muscles, phase 2 (assisted mode) where the robot provides compensatory force for incomplete movements, and phase 3 (strengthening mode) where the robot applies resistance to build muscle strength. The robot operates in passive, assistive, and resistive modes. Force-sensitive resistor (FSR) sensors measure interaction forces, and control is implemented via ATMEGA 32 microcontroller. Simulation and experimental trials with male and female participants were conducted. A microcontroller regulates the torque, force, angular acceleration, angular velocity and angular magnitude and direction using a PID control strategy, which is applied in accordance with therapeutic protocols. Experimental results demonstrate that the system effectively reduces stiffness, assists movement completion, and strengthens muscles through controlled resistance. The robot achieves maximum torque of 1.00 N·m, angular velocity 0.55 rad/s, and high repeatability (intraclass correlation coefficient (ICC) b 0.98 . Mode C shows active engagement with performance approaching reference values. Automating rehabilitation improves treatment efficiency and accessibility, offering a promising solution for patient recovery. The system provides adaptive, reliable, and gender-independent wrist rehabilitation, demonstrating clinical potential. The developed 3-DOF wrist rehabilitation robot with AFC-PID control achieves a maximum torque of 1.00 N·m, angular velocity of 0.55 rad/s, and reduces perceived joint stiffness by up to 15 %, demonstrating precise, adaptive assistance across passive, assistive, and resistive modes.
Preface MEV Vol 17 Iss 1 Yanuandri Putrasari
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

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Abstract

A new multilevel buck-boost inverter structure using six active switches Leonardus Heru Pratomo; Florentinus Budi Setiawan; Sushil Paudel
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1262

Abstract

Generally, multilevel inverters function as voltage step-down or step-up converters. This paper discussed a new type of multilevel inverter, specifically five-level and seven-level designs that use six active switches, which can increase or decrease the output voltage. The first study on using equal DC sources (E + E), known as symmetric, in the five-level setup for adjusting voltage was conducted, and then it was expanded to seven levels using an uneven DC source (2E + E), called asymmetric, with a new control method that works differently for each function. This multilevel voltage step-up (boost) and step-down (buck) inverter fundamentally has two components: a DC voltage level generator and a voltage step-up and polarity generator. This work provides a detailed look at how the multilevel voltage boost and buck inverter is built to show the features of the suggested design. Simulation data is provided to confirm how well each proposed design works with five-level and seven-level voltage increases and decreases in an inverter, using the sinusoidal pulse-width modulation (PWM) index and PWM duty cycle for better understanding. By the simulation, the total harmonic distortion (THD) value of the inverter when it operates as a buck is 1.26-1.32 %, and when it operates as a boost, it is 1.32-1.36 %. These values are still below 5 % in accordance with IEEE 519 standards and demonstrate a unity power factor.
Appendix MEV Vol 17 Iss 1 Yanuandri Putrasari
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

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Abstract

Fractional tent map - chaotic horse herd optimization for global MPPT under partial shading conditions Rachma Prilian Eviningsih; Ewa Ari Irwansyah; Epyk Sunarno; Moh. Zaenal Efendi; Novie Ayub Windarko; Anggara Trisna Nugraha
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 17, No 1 (2026)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55981/j.mev.2026.1423

Abstract

Photovoltaic efficiency is frequently compromised by physical obstructions, resulting in partial shading conditions. This non-uniform irradiance condition severely distorts system characteristics by inducing multiple power peaks. This study proposes a novel fractional tent map-chaotic horse herd optimization (FTM-CHHO) algorithm for global maximum power point (GMPP). By integrating fractional-order memory and chaotic maps, FTM-CHHO enhances global search capabilities and prevents entrapment in local maxima. The method was rigorously validated through simulations and hardware experiments using a SEPIC converter. Simulations demonstrated that FTM-CHHO achieved 99.52 % to 100 % tracking accuracy with rapid convergence times of 0.32 to 0.62 s. Furthermore, hardware tests under real-world shading confirmed its robustness, maintaining 95.54 % to 98.26 % accuracy and converging within 10.1 s. FTM-CHHO significantly outperformed perturb and observe (P8O) and standard horse herd optimization (HHO). These findings confirm that FTM-CHHO provides a highly reliable, fast, and efficient solution for maximizing solar energy extraction under complex environmental variability.

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