Second Order Electromechanical Step Response Modeling of EMMS-AS-70-SK-HV-RM with Closed Loop Control & Model Reduction

Abstract

This paper presents a detailed second-order electromechanical modeling approach of the EMMSAS-70-SK-HV-RM motor, focusing on its step response under closed-loop control conditions. The purpose
of this research is to simplify the complex dynamics of the motor system into an efficient mathematical
model that preserves key characteristics of the motor’s transient and steady-state behavior. A step input
was applied to the system, and the resulting data were used to derive a second-order transfer function that
accurately describes the motor response. The modeling process involved system identification techniques
to match the theoretical response with the actual experimental data.
The closed-loop configuration was implemented to ensure stability and repeatability in the motor response,
allowing for more consistent modeling. Following the development of the full-order model, model reduction
techniques were applied to further simplify the system for control and simulation purposes. The reducedorder model retains the essential dynamics while eliminating redundant or negligible parameters, thereby
improving computational efficiency and control design simplicity.
The performance of both the full-order and reduced-order models was evaluated by comparing their step
responses against experimental data. Results show that the reduced second-order model is capable of
closely approximating the real motor behavior with minimal error, validating the effectiveness of the model
reduction strategy. This work demonstrates that second-order modeling combined with model reduction
can offer a practical and reliable approach for motor control system design, especially in applications
requiring precise motion control such as robotics, automation, and industrial servo systems. Overall, the
findings of this study contribute to a better understanding of motor system dynamics and highlight the
importance of efficient modeling in modern control system engineering.