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Advances in Mathematical Modeling for Robotic Systems: Dynamics, Stability, Optimization and Control

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".

Deadline for manuscript submissions: closed (31 January 2026) | Viewed by 1542

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Department of Information Systems & Analytics, Affiliated Faculty at Louisville Automation Research and Robotics Institute (LARRI), University of Louisville, Louisville, KY 40292, USA
Interests: robotics; human–machine collaboration
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Special Issue Information

Dear Colleagues,

This Special Issue investigates the pivotal role of mathematical modeling in advancing robotic systems. We examine how mathematical models are essential for the stability analysis, design, optimization, and control of robots across various applications. We invite contributions that present innovative modeling techniques, stability analysis, simulation studies, optimization techniques, control algorithms, and applications that push the boundaries of robotic technology. This Special Issue encompasses a wide range of topics, from fundamental theoretical developments to practical implementations in fields such as industrial automation, medical robotics, service robotics, and aerial robotics. Our goal is to enhance the understanding of how mathematical models can drive more efficient, intelligent, and autonomous robotic systems.

Dr. Madan Mohan Rayguru
Guest Editor

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Keywords

  • mathematical modeling
  • robotics
  • dynamics
  • stability
  • simulation
  • control
  • optimization

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Published Papers (1 paper)

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Research

30 pages, 4550 KB  
Article
Robust Controller Design Based on Sliding Mode Control Strategy with Exponential Reaching Law for Brushless DC Motor
by Seyfettin Vadi
Mathematics 2026, 14(2), 221; https://doi.org/10.3390/math14020221 - 6 Jan 2026
Viewed by 975
Abstract
This study presents a comprehensive performance analysis of four different control strategies, Proportional–Integral (PI), classical Sliding Mode Control (SMC), Super-Twisting SMC (ST-SMC), and Exponential Reaching Law SMC (ERL-SMC), applied to the speed regulation of a Hall-effect sensored Brushless DC (BLDC) motor. A mathematically [...] Read more.
This study presents a comprehensive performance analysis of four different control strategies, Proportional–Integral (PI), classical Sliding Mode Control (SMC), Super-Twisting SMC (ST-SMC), and Exponential Reaching Law SMC (ERL-SMC), applied to the speed regulation of a Hall-effect sensored Brushless DC (BLDC) motor. A mathematically detailed BLDC motor model, three-phase inverter structure with safe commutation logic, and a high-frequency PWM switching scheme were implemented in the MATLAB/Simulink-2024a environment to provide a realistic simulation framework. The control strategies were evaluated under multiple test scenarios, including variations in supply voltage, mechanical load disturbances, reference speed transitions, and steady-state operation. The comparative results reveal that the classical SMC and PI controllers suffer from significant oscillations, overshoot, and limited disturbance rejection capability, especially during voltage and load transients. The ST-SMC algorithm improves robustness and reduces the chattering effect inherent to first-order SMC but still exhibits noticeable oscillations near the sliding surface. In contrast, the proposed ERL-SMC controller demonstrates superior performance across all scenarios, achieving the lowest steady-state ripple, the shortest settling time, and the most stable transition response while significantly mitigating chattering. These results indicate that ERL-SMC is the most effective and reliable control strategy among the evaluated methods for BLDC speed regulation, which requires high dynamic response and disturbance robustness. The findings of this study contribute to the advancement of SMC-based BLDC motor control, providing a solid foundation for future research that integrates observer-based schemes, adaptive tuning, or real-time hardware implementation. Full article
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