Abstract
An adaptive inferential algorithm is developed for estimation and control of multirate systems. The output y is measured J times slower than the secondary process output v and the input u, but an output estimate y e is produced at each sampling interval of v and u. Compared with previous work on multirate inferential systems, the proposed algorithm has a more formal theoretical basis. For example, the output y is related to the secondary output v not only through external stochastic disturbances but also through the internal system structure. Convergence properties are formally proven for the case of zero external stochastic disturbances, and a simplified algorithm is proposed for practical applications. Simulated results illustrate the convergence properties of the algorithm and the improvement obtained in simple feedback control systems.
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