State analytical predictor for systems with multiple time delays

An approach for the design of a dead-time compensator for processes with time delays is presented. The proposed algorithm deals with multivariable state-space models instead of input-output models and utilizes not only a single delay but also distributed delays in the feedback loop. Both the continuous-time and discrete-time versions of the algorithm are derived. The design strategy of the controller is based on the approach of LQG design. It is incorporated into the dead-time compensation technique of the analytical predictor, which uses the process model directly to predict the effect of input variables on the process outputs. By introducing an integral action into the observation system, the steady-state observation error of the inaccessible load inputs converges to zero. This permits us to perform disturbance prediction and compensation within a single design. Theoretical analysis shows that this control strategy fully removes time delay elements from a system characteristic equation in the ideal situation of a system without model-plant mismatch and/or noise measurements. By the estimation and prediction of the unknown plant-input disturbances, the capability for rejecting input disturbances has also been improved. The control structure developed is shown to have the same closed-loop relationships as the linear quadratic feedback structure for a system without lime delays. The potential benefits of the proposed controller are demonstrated by the control problem of an industrial grinding system studied previously by Niemi et al. (1982) and Ylinen et al. (1987), which is a challenging problem for MPC-type algorithms.