LFT Model Generation Via L1-Regularized Least Squares
The paper presents a general approach to approximate a nonlinear system by a linear fractional representation (LFR), which is suitable for LFT-based robust stability analysis and control design. In a first step, the nonlinear system will be transformed into a quasi linear parameter varying (LPV) system. In the second step, the nonlinear dependencies in the quasi-LPV, which are not rational in the parameters, are approximated using polynomial fitting based on l1-regularized least squares. Using this approach an almost Pareto front between the accuracy and complexity of the resulting LFR can be efficiently obtained. The effectiveness of the proposed method is demonstrated by applying it to a nonlinear missile model of industrial complexity.