Abstract
A multivariable adaptive control scheme has been studied and evaluated with the help of a phenomenological simulator which was calibrated on a laboratory grinding circuit. The adaptive control scheme includes a Kalman filter, an adaptive mechanism, and a control law. The adaptive mechanism is based on the estimation of a fundamental coefficient of the process since a direct identification of the whole set of parameters is impossible due to the large size of the state-space model. The control law that minimizes a quadratic criterion is obtained by dynamic programming. Simulated results show that the control law exhibits good performances. The control scheme is robust and is able to face 100% change on grinding rate parameters, without deterioration of the performances.
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