Analog-digital systems for adaptive measurements and parameter estimation of noisy processes

The theoretical framework and principles of designing a new class of highly effective analog-digital computer-aided measurement systems are presented. The proposed approach enables the designers to determine uniquely the optimal structure, parameters and characteristics of measurement systems working in the presence of noises and disturbances as well as to carry out the comprehensive analysis of their work. The approach is based on the new idea of the nonlinear adaptively controlled (smart) sensor. The algorithms for optimal processing of the measured data and estimating unknown parameters of analyzed processes or objects, coupled with the optimal adaptive control of the sensor parameters, are derived. The superiority of measurement systems with adaptively controlled sensors over the conventional ones employing nonadaptive sensors is shown. The main theoretical results and conclusions are verified and confirmed via simulations taking as an example the string-frame accelerometer