Optimal input signals for nonlinear-system identification

Abstract
The choice of input signal in an identification experiment has a significant bearing on the final result. At one extreme, an input can result in violent system disturbances and the subsequent loss of product or damage to the system. At the other extreme, an input can be so conservative as to yield little or no information about the system's dynamic behaviour. The optimal input signal achieves a compromise between these extremes. This paper describes a design procedure for synthetising optimal input signals. A state-space description of the system is used, and the optimal input is chosen to minimise the variance of the parameter and state estimates. The method applies to both linear and nonlinear systems and the case of both white and coloured output noise has been considered. The optimal input signals are shown to result in a significant improvement in the identification accuracy.

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