Biomathematical Modeling of Electromechanical Systems: A Computational Approach to Bio-Inspired Engineering Design
Year: 2026
Type: article
Abstract: This paper introduces a bio-inspired electromechanical actuator computational bio-mathematical model which transforms normalized electrical excitation into activation, force and displacement response. Three dynamic state variables were formulated in the system: displacement, velocity, and activation and mechanical behavior have been modeled in terms of a mass-stiffness-damping structure and biological-style activation modeled by first-order dynamics. The target biological motion was a sinusoidal reference trajectory with an amplitude of 0.02 m and frequency of 1.2 Hz. Simulation of the coupled differential equations was done in 8 s with 0.01 s time step, which resulted in 801 discrete time samples. Differentiation evolution was used to optimize four design variables; stiffness, damping, maximum actuator force, and time constant activation. The optimized parameters were k = 4.0486704006, c = 0.0225310547, Fmax = 0.0332727779, and tau = 0.0200000000. Root mean square error, an energy proxy, and a composite objective were used to assess model performance. The optimized simulation produced an RMSE of 0.0082268868 m, energy proxy of 3.1120588408, and objective score of 0.0704680636. The sensitivity analysis revealed that stiffness was the most influential parameter that influenced tracking accuracy, as compared to damping that had a relatively weak effect. The results indicate that a small-scale differentiation-equation-based framework can assist with the initial-stage bio-inspired electromechanical design, parameter screening and computational analysis prior to physical prototyping. This method provides a numerically interpretable foundation of connecting excitation, activation, and mechanical force production, as well as optimal actuator motion based on simplified assumptions.
Source: Computer and decision making.
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7222800366