Abstract
The paper deals with a possible extension of the existing minimum variance (MV) and self-tuning (ST) control strategies for a class of distributed parameter systems (D.P.S.). The distributed output signal (D.O.S.) of the process is transformed to a single variable using the spatial weighted average (S.W.A.) transformation. If the process parameters are known it is easy to derive a minimum variance controller. In case of unknown process parameters the recursive least-squares technique is applied to estimate the parameters of the controller directly. The algorithm and its convergency properties are demonstrated by several computer simulations.
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