Closed-loop subspace Predictive Control for Linear Parameter Varying systems (ii) - a supervisory and robust approach

The paper explores the advantage of Subspace Predictive Control for Linear Parameter Varying systems (SPC LPV) in supervisory and in robust control scheme. Closed-loop subspace identification technique is used to identify the I/O LPV predictor for optimal control application. This type of the SPC LPV is a data driven approach. The predictor is augmented with the a-priori known and primary-loop controller information. Hence, instead of replacing the existing controller in the loop, a supervisory SPC LPV is proposed in the paper. Moreover, robust extension of the nominal and optimal SPC LPV is formulated taking the worst case future scheduling parameter variation into account. The application of the proposed control schemes on a nonlinear DC motor illustrates the supervisory and the robust nature of the SPC LPV.