A Linear-Quadratic-Gaussian Control Algorithm for Sulphide Ore Grinding

Abstract

The paper suggests an algorithm for the multi variable control of an lndustrial sulphide ore grinding plant. The algorithm is based on the linear-quadratic gaussian control theory with a moving time horizonThe dynamic process model with two inputs and two outputs is obtained by fitting simple low order linear time-invariant models to measured inputoutput pairs. Characteristic to the model are the long time delaysThe model is brought to the state space form, in which the time delays are described by additional state components. The inputs are replaced by input increments, for the purpose of avoiding imbalances of stationary values and of assigning quadratic costs to input changesBecause of disturbances both in the process and in the measuring equipment Kalman filter is used for state estimation. In order to carry out the setpoint changes faster, the estimated state is corrected by tne corresponding change of coordinatesThe control algorithm has been tested both by simulation runs and by implementation in the control of the plant. The weighting and covariance matrices were used as tuning parameters. The test runs showed that the algorithm can be tuned rather easily and satisfactory results were obtainedThe steady state interactions were almost completely compensated and the transient interactions were within acceptable limits