cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Alfian Ma'arif
Contact Email
alfian_maarif@ieee.org
Phone
-
Journal Mail Official
alfian_maarif@ieee.org
Editorial Address
Jl. Empu Sedah No. 12, Pringwulung, Condongcatur, Kec. Depok, Kabupaten Sleman, Daerah Istimewa Yogyakarta 55281, Indonesia
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
Control Systems and Optimization Letters
Published by Peneliti Teknologi Teknik Indonesia
ISSN : -     EISSN : 29856116     DOI : 10.59247/csol
Core Subject : Science, Engineering,
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
Control Systems and Optimization Letters is an open-access journal offering authors the opportunity to publish in all fundamental and interdisciplinary areas of control and optimization, rapidly enabling a safe and sustainable interconnected human society. Control Systems and Optimization Letters accept scientifically sound and technically correct papers and provide valuable new knowledge to the mathematics and engineering communities. Theoretical work, experimental work, or case studies are all welcome. The journal also publishes survey papers. However, survey papers will be considered only with prior approval from the editor-in-chief and should provide additional insights into the topic surveyed rather than a mere compilation of known results. Topics on well-studied modern control and optimization methods, such as linear quadratic regulators, are within the scope of the journal. The Control Systems and Optimization Letters focus on control system development and solving problems using optimization algorithms to reach 17 Sustainable Development Goals (SDGs). The scope is linear control, nonlinear control, optimal control, adaptive control, robust control, geometry control, and intelligent control.
Arjuna Subject : Teknik (semua kategori) - Teknik Kontrol dan Sistem
Articles 154 Documents
 12   13   14   15   16 
Comparative Evaluation of Transfer Function and Detailed Switching Models for a PID-Controlled Single-Phase DC–AC Conversion System Fifin Nugroho; Hari Maghfiroh; Warindi Warindi; Fahmizal Fahmizal
Control Systems and Optimization Letters Vol 4, No 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i2.324

Abstract

Transfer-function (TF) models are widely used in power electronics because of their simplicity and suitability for controller design. However, their ability to represent practical converter behavior is limited since switching actions and nonlinear effects are neglected. This paper presents a comparative evaluation of transfer-function and detailed switching models for a PID-controlled single-phase inverter system consisting of a DC–DC boost converter and a full-bridge inverter employing unipolar sinusoidal pulse width modulation (SPWM). The system is designed to convert a 46 VDC input into a regulated 220 VAC (RMS), 50 Hz output. Both models were developed in MATLAB/Simulink and evaluated under identical operating conditions. The results show that the TF model provides a computationally efficient representation suitable for preliminary controller design, while the detailed switching model captures switching-induced ripple, transient dynamics, and harmonic distortion. The detailed model achieved stable 220 VAC operation with a total harmonic distortion (THD) of 1.91%, satisfying IEEE Standard 519 requirements. The comparative analysis indicates that controller parameters obtained from the TF model can provide a useful initial tuning reference before refinement in the detailed switching model. Since the study is based exclusively on simulation, experimental validation remains necessary. The results suggest that TF models are suitable for early-stage controller development, whereas detailed switching models are required for realistic performance assessment and validation.
Pattern Analysis on Multi-Sensor Networks: Short-Term Forecasting at Parangtritis Coastal, Yogyakarta, Indonesia Haris Imam Karim Fathurrahman; Choirul Fajri; Chin Li-Yi; Khoirudin Wisnu Mahendra
Control Systems and Optimization Letters Vol 4, No 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i2.333

Abstract

Reliable microclimatic records are a prerequisite for evidence-based agricultural planning, yet high-resolution ground-truth datasets for tropical coastal environments remain scarce in the Indonesian literature. This study analyzes six months (December 2025 – May 2026) of 10-minute interval observations across 18 meteorological variables from the Parangtritis Automated Weather Station (AWS), Bantul Regency, Yogyakarta, Indonesia. Rainfall was reconstructed via a differential method from the cumulative station counter, yielding a period total of 1748.4 mm over 180 days. Of these, 112 days (66.1%) recorded measurable precipitation, punctuated by seven dry-spell episodes; the longest extended 12 consecutive days (5–16 May 2026). Schmidt-Ferguson classification returned Q = 20%, placing the site in Climate Type B (Wet/Basah). Reference evapotranspiration (ET₀, Hargreaves–Samani) averaged 10.20 mm/day (total: 1796.0 mm), and a PDSI proxy indicated extreme drought conditions by the close of the observation period (PDSI = −7.45), a deficit attributable primarily to persistently high ET₀ demand rather than rainfall deficiency per se. Cross-correlation analysis identified relative humidity as the dominant concurrent temperature predictor (lag 0; r = −0.676). An XGBoost model achieved short-term temperature forecasting accuracy of MAE = 0.56°C and RMSE = 0.71°C (R² = −1.419, reflecting the site's narrow diurnal thermal variance rather than model failure). Prophet projected sharply reduced rainfall for June–August 2026 (0.25–4.77 mm), which the generic staple-crop suitability framework scores as Not Recommended, reflecting unsuitability for rainfed rice, yet these drier conditions are agronomically favourable for shallot in coastal Yogyakarta.
Robust Parameter Identification and Control Modeling of Low-Cost Brushed DC Motors Using the Nelder-Mead Algorithm Channareth Srun; Mengseu Pheng; Sovathana Um; Chivon Choeung; Seven Siren; Sros Nhek
Control Systems and Optimization Letters Vol 4, No 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i2.321

Abstract

Brushed DC motors are widely used in next-generation automation systems due to their low complexity and ease of control. However, more affordable models often lack sufficient information about their detailed parameters, which makes accurate control and modeling difficult. This paper presents an estimation method for the main parameters of a low-cost brushed DC motor using the Nelder-Mead algorithm. Real-time measurements of speed were obtained through Arduino-based testing, followed by parameter estimation using MATLAB and Simulink. The estimated parameters include armature resistance, inductance, moment of inertia, viscous damping coefficient, back electromotive force constant, and torque constant. The estimated results, validated strictly against a high-specification reference motor datasheet, demonstrate strong accuracy in critical mechanical parameters. Specifically, the algorithm estimated the torque constant with a minimal error of 0.17% and the viscous damping coefficient with an error of 4.8%. However, due to the inherent structural unidentifiability when relying solely on macroscopic speed measurements, electrical parameters such as armature resistance, inductance, and moment of inertia exhibited severe deviations ranging from 39.6% to 52.7%. While the objective function's inability to fully decouple these intertwined variables restricts isolated physical parameter extraction, the method effectively captures the equivalent macroscopic dynamic behavior. The predictive validity of the proposed method was further confirmed by implementing a PI controller based on the estimated transfer function. The experimental results confirm that despite internal physical parameter discrepancies, the algorithm provides an equivalent and robust dynamic model that significantly improves motor performance in control systems. This work proposes an inexpensive and efficient system identification solution for low-cost motor control characterization.
Comparing LQR, SMC, and Backstepping for Active Suspension: Robustness, Energy Efficiency, and Frequency Response Ali Aniss Ebrahim
Control Systems and Optimization Letters Vol 4, No 2 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i2.319

Abstract

While active suspension systems have advanced significantly, the literature still lacks a systematic compara tive framework that integrates time-domain robustness analysis, frequency-domain vibration isolation, and operational constraints such as actuator saturation. This study presents a comparative framework to bridge this gap through a quantitative evaluation of three advanced control strategies: Linear Quadratic Regulator (LQR), Sliding Mode Control (SMC), and Backstepping. The strategies were evaluated under multiple test scenarios, including: a step signal (0.05 m for 0.2 s), a 0.02 m amplitude sine wave with varying frequencies between 0.5 and 10 Hz, a random wave, ±20% variations in system parameters, and simulated actuator saturation constraints at ±1500 N. The SMC controller demonstrated exceptional robustness under uncertainty, achieving a 34.2% improvement in suspension deflection, while the LQR controller demonstrated superior energy efficiency, outperforming SMC by 28.5%. Frequency response analysis revealed that LQR is optimal in the low frequency band (0–2 Hz), while SMC excels in the mid band (2–8 Hz). Analysis of variance (ANOVA) confirmed statistically significant differences between the strategies (F(2,87) = 24.36, p 0.001). This framework provides a quantitative trade-off model that guides designers to: use SMC for applications requiring high robustness under uncertain conditions (such as vehicles operating on varying terrain), use LQR when energy efficiency is a top priority (such as electric vehicles), and use Backstepping as a compromise that ensures guaranteed mathematical stability with balanced performance.

Page 16 of 16 | Total Record : 154

 12   13   14   15   16 

Filter by Year

2023 2026


Reset
Filter By Issues
All Issue Vol 4, No 2 (2026) Vol 4, No 1 (2026) Vol 3, No 3 (2025) Vol 3, No 2 (2025) Vol 3, No 1 (2025) Vol 2, No 3 (2024) Vol 2, No 2 (2024) Vol 2, No 1 (2024) Vol 1, No 3 (2023) Vol 1, No 2 (2023) Vol 1, No 1 (2023) More Issue