In the framework of our research on high-gain observers for nonlinear systems we have reached the final development step consisting of a real-time implementation in Linux. The results presented in this paper were obtained using RTAI-lab and the Scilab/Scicos CACSD environment on a series-connected DC motor. We introduce the three algorithms we implemented as 1) the classic high-gain Luenberger, 2) the high-gain extended Kalman filter, and 3) our newly proposed adaptive-gain extended Kalman filter (AEKF). This article is a comprehensive description of our real-time applied mathematics experiment.

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