Abstract
This paper explores empirical modeling of McKibben muscle in characterizing its hysteresis behavior and nonlinearities during quasi-static, quasi-rate, and historic dependencies. The unconventional materials-based actuating system called McKibben muscle has excellent properties of power-to-weight ratio, which could be used in rehabilitation orthosis application for condition monitoring, physical enhancement, and rehabilitation therapy. McKibben muscle is known to exhibit hysteresis behavior and it is rate-dependent (the level of hysteresis depends closely on rate of input excitation frequency). This behavior is undesirable and it must be considered in realizing high precision control application. In this paper, the nonlinearities of McKibben muscle is characterized using empirical modeling with multiple correction functions such as shape irregularity and slenderness. A particle swarm optimization (PSO) method is used to determine the best parametric values of the proposed empirical with modified dynamic friction model. The LabVIEW and MATLAB platforms are used for data analysis, modeling and simulation. The results confirm that this model able to significantly characterize the nonlinearities of McKibben muscle while considering all dependencies.
Highlights
McKibben muscle plays an important role in the development of assistive rehabilitation robotics system
The performance of dynamic modeling of McKibben muscle was evaluated based on comparison test of empirical modeling and hysteresis data
Additional correction functions were proposed to increase the adaptability of the dynamic friction model when tested with all dependencies
Summary
McKibben muscle plays an important role in the development of assistive rehabilitation robotics system. Due to its clear advantages such as low weight, structural flexibility, compactness, and inherent compliance compared to other types of artificial muscles, the researcher’s interest in this field has grown exponentially in past decade [1,2,3]. This growth due to the challenges it provides in resolving nonlinearity behaviors and difficulties in controlling such systems. The inherent nonlinearity behaviors of McKibben muscle present because of nonlinear relationship in between its contracting force, contracting length and pressure [4,5,6]. Numerous control strategies were considered to resolve nonlinearity problems in
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