The recursive generalized predictive feedback control: theory and experiments

The proposed adaptive control algorithm combines the recursive least-squares system identification algorithm and the generalized predictive control (GPC) design algorithm, referred to as recursive generalized predictive control (RGPC.) In the GPC design process, the prediction horizon and control horizon are the constants to be chosen. Two new parameters are defined to describe the effects of the prediction and control horizons and those parameters provide the effective ranges of the horizons. The RGPC algorithm adjusts the control penalty based on the stability of a closed-loop system model. A time-varying algorithm for the control penalty allows to design an aggressive controller. The multi-sampling rate algorithm is added between the system identification and the control design in order to design a higher order controller. The RGPC algorithm is applied to three different systems: a cantilevered beam, a sound enclosure, and an optical jitter suppression testbed.