Abstract
This paper proposes piecewise affine (PWA) virtual sensors for the estimation of unmeasured variables of nonlinear systems with unknown dynamics. The estimation functions are designed directly from measured inputs and outputs and have two important features. First, they enjoy convergence and optimality properties, based on classical results on parametric identification. Second, the PWA structure is based on a simplicial partition of the measurement space and allows one to implement very effectively the virtual sensor on a digital circuit. Due to the low cost of the required hardware for the implementation of such a particular structure and to the very high sampling frequencies that can be achieved, the approach is applicable to a wide range of industrial problems.
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