Abstract
In process control, it is usual to assume that a single linear model can describe a real system, although uncertainty in the model parameters must be considered for control applications. As a consequence, a vast body of work has appeared that addresses the problems posed by this situation via, either adaptive control or robust, control. The present work is focused on robust predictive control (RPC), and proposes a new approach based on Laguerre filters modeling. It is shown that this way of modeling can bring some advantages in the RPC context. The approach is developed for constrained systems. Simulation results are presented to illustrate the new RPC algorithms.
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