A linear-quadratic-Gaussian control algorithm for sulphide ore grinding

Abstract

The paper suggests an algorithm for the multivariable control of an industrial sulphide ore grinding plant. The algorithm is based on the linear-quadratic-Gaussian control theory with a moving time horizon. The dynamic process model with two inputs and two outputs is obtained by fitting simple low order linear time-invariant models to measured input-output pairs. Characteristic to the model are long time delays. The 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 changes. Because of disturbances both in the process and in the measuring equipment, a Kalman filter is used for state estimation. The control algorithm was tested both by simulation runs and by implementation in the control of the plant. The test runs showed that the algorithm can be tuned rather easily, and satisfactory results were obtained. The steady-state interactions were almost completely compensated and the transient interactions were within acceptable limits.