MSc Thesis Defense: Görkem Gemalmaz, PASSIVITY AND PERFORMANCE OF HAPTIC RENDERING WITH FRACTIONAL-ORDER MODELS, Date & Time: 22 July, 2026 – 4:00 PM, Place: FENS L063
PASSIVITY AND PERFORMANCE OF HAPTIC RENDERING
WITH FRACTIONAL-ORDER MODELS
Görkem Gemalmaz
Mechatronics Engineering, MSc Thesis, 2026
Thesis Jury
Prof. Volkan Patoglu (Thesis Advisor)
Asst. Prof. Melih Turkseven
Prof. Çagatay Basdogan
Date & Time: 22nd July 2026 – 04.00 PM
Place: FENS L063
Keywords: Physical human-robot interaction, haptic rendering, fractional-order modeling, passivity, human-in-the-loop optimization.
Abstract
The realistic haptic rendering of viscoelasticity is vital in domains such as medical simulation, where biological tissues exhibit complex time-dependent viscoelastic behavior. The fractional-order models offer a concise representation of such dynamics by effectively capturing memory-dependent effects. Nevertheless, incorporating fractional-order dynamics into real-time interaction control is not trivial. Discrete-time realizations of fractional operators can only be implemented under a finite truncation of the memory kernel, resulting in a model with a large discrete parameter space. Accordingly, the analysis and parameter selection for the resulting sampled-data system with fractional-order models become significantly more challenging. In this study, we first derive closed-form expressions to ensure the passivity of haptic rendering with a fractional-order standard linear solid (FO-SLS) model based on the Grünwald-Letnikov derivative under short-memory discretization. We also provide symbolic expressions for the effective impedance of FO-SLS models. Our results constitute a unifying framework that generalizes previously reported results for integer-order models. Second, we demonstrate that the parameters of frictional order models can be effectively optimized through qualitative feedback-based human-in-the-loop optimization, ensuring consistently high realism ratings. Third, we provide evidence from psychophysical experiments that fractional-order models lead to perceptually improved haptic rendering compared to their integer-order viscoelastic model alternatives. Finally, we enhance the passive impedance rendering range of haptic interfaces by augmenting them with physical fractional-order electrical dampers. Overall, our contributions pave the way for a more principled use of fractional-order viscoelastic models for realistic haptic rendering and in physical human-robot interaction.