This paper is concerned with modelling of the front end of an aircraft pilot flight control system's behav iour using a nonlinear system identification technique known as parallel cascade identification. Using this technique, we are able to model a critical part of a pi lot flight control system with sufficient accuracy to meet the objective test requirements of the U.S. Fed eral Aviation Administration for certifying full flight simulators. Traditional approaches to modelling such aircraft systems involve extensive analytical studies of the design of the system, lengthy and detailed empiri cal testing and recording of data from the physical system, and then considerable analysis to fit paramet ric models to the data. The approach presented in this paper virtually eliminates the need for analysis of the system in question, significantly reduces the number of signals that need be recorded from the real aircraft flight control system, and provides an extremely fast method of identifying the mathematical model based on these data. Overall, the time and costs associated with building an effective model are greatly reduced.
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