Performance analysis of control allocation using data‐driven integral quadratic constraints

A new method is presented for evaluating the performance of a nonlinear control allocation system within linear loop. To that end, worst-case gain analysis problem formulated can be readily solved by means well-established methods from robustness using integral quadratic constraints (IQCs). It exploits fact systems are in general memoryless mappings bounded IQCs. data-driven approach used to find an optimal bound input/output mapping allocation. Additionally, iterative procedure based on local IQCs introduced determine meaningful sampling limits less conservative yet accurate results. The effectiveness proposed shown at example actively controlled flexible wing wind tunnel.