A New Input Constrained Quadratic Tracker for an Unknown Sampled-Data System with an Input to Output Direct Transmission Term

A new quadratic digital tracker for efficient tracking control of an unknown sampled-data system with a direct transmission term from an input to output and subject to input constraints is proposed in this paper. First, the observer/Kalman filter identification (OKID) method is utilized to identify an appropriate (low-) order state-space innovation model with a feed-through term, equivalent to the unknown linear system; this identified model is used for the design of the controller and observer. The newly proposed inputconstrained quadratic digital tracker also comprises a new systematic mechanism for tuning the weighting matrix in the cost function of interest. Further, the realizable current output-based digital observer with a direct transmission term is developed for the system whose states are immeasurable. An illustrative example is given to demonstrate the effectiveness of the proposed approach.