PROJECT TITLE :

An SIMO Nonlinear System Approach to Analysis and Design of Vehicle Suspensions

ABSTRACT:

Vehicle suspension (or vibration management) systems are sometimes inherently nonlinear and can be modeled as single input multiple output (SIMO) system. In this paper, parametric convergence bounds for Volterra series enlargement of nonlinear systems described by a SIMO nonlinear auto-regressive with exogenous inputs model are studied within the frequency domain, that will clearly indicate the parametric range in that a given nonlinear system includes a convergent Volterra series enlargement, referred to as parametric sure of convergence (PBoC). With the resulting PBoC of characteristic parameters, nonlinear systems with a nonlinear multiobjective performance (MOP) perform can then be analyzed within the frequency domain using a nonlinear characteristic output spectrum method based on the Volterra series expansion. To demonstrate the results and methodology above, a vehicle suspension system, which is taken as a typical SIMO nonlinear system with a MOP perform to optimize, is investigated. The results demonstrate a scientific and novel technique for nonlinear analysis and style.


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