Abstract
System performance and efficiency depends on the stability criteria. The lower limb prosthetic model design requires some prerequisites such as hardware design functionality and compatibility of the building block materials. Effective implementation of mathematical model simulation symmetry towards the achievement of hardware design is the focus of the present work. Different postures of lower limb have been considered in this paper to be analyzed for artificial system design of lower limb movement. The generated polynomial equations of the sitting and standing positions of the normal limb are represented with overall system transfer function. The behavioral analysis of the lower limb model shows the nonlinear nature. The Euler-Lagrange method is utilized to describe the nonlinearity in the field of forward dynamics of the artificial system. The stability factor through phase portrait analysis is checked with respect to nonlinear system characteristics of the lower limb. The asymptotic stability has been achieved utilizing the most applicable Lyapunov method for nonlinear systems. The stability checking of the proposed artificial lower extremity is the newer approach needed to take decisions on output implementation in the system design.
Highlights
Nature is nonlinear as the responses of the physical systems in the applied fields show nonlinear behavior
For further stability checking, the Lyapunov stability method is strongly recommended for nonlinear systems
The nonlinear control systems have gained a challenging position in the technological development of the biomedical application field
Summary
Nature is nonlinear as the responses of the physical systems in the applied fields show nonlinear behavior. Nonlinear controller can compensate the unwanted effects on the system. An important research field for nonlinear control systems is to design controllers to deal with uncertainty, mainly due to the unavailability of parametric information of the models and external disturbances. Hard nonlinearities such as dead-zones, hysteresis and saturation do not permit linear approximation of real-world systems. The method of approximation deals with the effects of nonlinearity. This can cause inaccuracy in the system. The effects of unwanted nonlinearities in the system should be analyzed to improve the dynamic performance of any real-time system development
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