Predictive control algorithms with guaranteed stability and asymptotic tracking

A model of the continuous steel casting process is developed and validated using open loop identification. Modifications are made to the identification algorithm to enhance accuracy of the estimated model. The GPC (generalized predictive control) algorithm is then implemented for mold level regulation of the casting process. Compensation of measurement noise by the standard GPC algorithm results in excessive controller activity. A modification to the GPC cost function is suggested to account for measurement disturbances by dynamically filtering the predicted free response of the process model before the total future response is computed and weighted in the GPC cost function. Experimental results indicate that regulation performance of the modified GPC in the presence of load disturbances is much better than conventional PI control. A lower bound on the costing horizon that results in closed loop stability under GPC is not known a priori. Sufficient conditions are presented for stability of closed loop systems that result from implementing solutions of the finite horizon LQ (linear quadratic) problem for arbitrary fixed costing horizons. On this basis, a class of predictive control laws referred to as SPC (stabilizing predictive control) that ensures stability of the closed loop system is proposed. For tracking reference signals with step changes, a controller structure is derived that achieves asymptotic tracking while preserving stability of the closed loop system. Simulation results that illustrate the stabilizing and asymptotic tracking properties of SPC for both minimum phase and nonminimum phase unstable plants are presented.; The features of certain continuous casting setups result in a periodic load disturbance that influences regulation of mold level. The design and implementation of a discrete time repetitive controller that is used for rejection of periodic load disturbances is described. When the period of the disturbance is not precisely known, a discrete time recursive scheme is used for identification of the period and the controller is tuned on-line. Experimental results that compare disturbance rejection properties of the self-tuning repetitive controller with those of PI control are presented.