Probabilistic Robust Parallel Design of the Subsystems Constituting a Complex System

Abstract

The design of complex systems, consisting of several subsystems and with performance specifications from multiple disciplines, in parallel was addressed in a previous publication using a Robust Parallel Design (RPD) approach. In this paper, RPD is extended and a Probabilistic Robust Parallel Design (PRPD) approach is proposed to handle cases where the statistical properties of uncertainties are known. Monte Carlo simulation is used to determine the value of a subsystem objective, given the known statistical distributions of uncertainties. Random search techniques (e.g., Simulated Annealing) can then be used to minimize the subsystem objective. PRPD is illustrated using a passive suspension design example of a half-car model. Copyright © 2005 IFAC

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