Optimum experimental design for identification of distributed parameter systems

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Abstract
A method to design optimal experiments for parameter estimation in distributed systems is given. The design variables considered are the boundary perturbation and the spatial location of measurement sensors. The design criterion used is the determinant of Fisher's information matrix. It is shown that suitable choice of these variables leads to improved parameter accuracy. Two examples are used to illustrate this method. The first example is concerned with sensor location for estimating the velocity of propagation and the damping coefficient of a vibrating string. The second example is concerned with the estimation of the thermal diffusivity and radiation constant for a heat diffusion process. It is also shown that the design philosophy can be applied to a wide class of systems described by partial differential equations.