Modeling and Simulation of Lower Limb Rehabilitation Exoskeletons: A Comparative Analysis for Dynamic Model Validation and Optimal Approach Selection

Accurate modeling and simulation of lower limb rehabilitation exoskeleton (LLRE) enables effective control resulting in enhanced performance and ensuring efficient rehabilitation. There are two primary objectives of this study. First is to validate the existing models and second is to identify the optimal modeling approach for exoskeletons. For validation, firstly a lower limb rehabilitation exoskeleton is modeled using three different modeling approaches which include analytical modeling, bond graph modeling, and modeling through Simscape (SS). Thereafter, dynamic responses of analytical and graphical modeling are compared with SS model using key dynamic response parameters, including rise time, peak time, and others. The SS-based physical model can be employed for validation because SS, unlike mathematical modeling, uses unit-consistent physical domain data and, therefore, serves as an intermediate step between mathematical modeling and hardware validation. Secondly, to identify the most suitable modeling approach, a structured and comprehensive comparison of different modeling approaches based on aspects such as control domain, complexity, ease of use, and other relevant factors is carried out. The results highlight the qualitative strengths and limitations of the three approaches. Previous studies focus on individual methods and lack such comparison. This work contributes to the validation of models and identification of an efficient and effective modeling methodology for LLRE. The findings reveal that Simscape™ is the most suitable approach for modeling LLREs as it provides multidisciplinary system modeling and supports real-time simulation. The validated model can now be employed for advancements in model-based control design. Moreover, the identified optimal approach provides an insight to researchers and engineers for model selection in early-stage design and control development of complex mechatronic systems. Future work includes comparison of dynamic responses with actual hardware responses to experimentally validate the effectiveness of the model for real-world patient assistance and mobility restoration.