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<p>This paper presents a new combination of intelligent PD (i-PD) controllers, designed using an ultra-local model and a sliding mode differentiator with a variable exponent (SMDVE), which is employed to estimate the unknown model. This new controller combination leverages real-time data to optimize performance under varying conditions. This approach enhances the controller’s performance across varying conditions to develop a robust, speedy, and high-precision controller for tracking trajectory and minimizing the controller’s energy consumption. The results demonstrate that incorporating a sliding mode differentiator with variable exponent in the i-PD controller enhances overall performance more significantly than implementing a low-pass filter scheme, particularly under dynamic disturbance conditions.</p>

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High-gain I-PD Controller Based on an Ultra-local Model with Sliding Mode Differentiator for Trajectory Tracking Performance

  • 期刊论文

  • 发表日期：

    2025年9月2日

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  • Dorsaf Elleuch,
  • Neila Mezghani Ben Romdanne,
  • Tarak Damak

摘要

This paper presents a new combination of intelligent PD (i-PD) controllers, designed using an ultra-local model and a sliding mode differentiator with a variable exponent (SMDVE), which is employed to estimate the unknown model. This new controller combination leverages real-time data to optimize performance under varying conditions. This approach enhances the controller’s performance across varying conditions to develop a robust, speedy, and high-precision controller for tracking trajectory and minimizing the controller’s energy consumption. The results demonstrate that incorporating a sliding mode differentiator with variable exponent in the i-PD controller enhances overall performance more significantly than implementing a low-pass filter scheme, particularly under dynamic disturbance conditions.