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Ali Aniss Ebrahim
University of Tartous
Aerospace Engineering Automotive Engineering Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Modeling of a Sliding Mode Controller to control the Tracking System for Solar Panels with Two Degrees of Freedom Ali Aniss Ebrahim
Control Systems and Optimization Letters Vol 4, No 1 (2026)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/csol.v4i1.277

Abstract

In this report, the design of a cascade Sliding Mode Controller (SMC) with a boundary layer for chattering attenuation is presented for a dual-axis solar tracking system. First, the theoretical background of this control method is presented. Then, using MATLAB/Simulink, the proposed controller is designed and simulated under various scenarios including step, sinusoidal trajectories, and external disturbances. The simulation results demonstrate high-precision tracking with a root mean square error (RMSE) of 0.15°, robust disturbance rejection, and a significant enhancement in electrical energy generation by up to 40% compared to a fixed-panel system.
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.
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