Optimal anti-aliasing filter based on multi criteria sampled-data ∞ control
Paper i proceeding, 2015
A systematic evaluation procedure is presented and applied to generate optimal anti-aliasing filters. It is based on multi criteria ∞ optimization, where sampled-data measures are introduced to capture the intersample behavior. The optimization scheme is based on linear matrix inequalities (LMIs) formulated in the delta operator, and the result is a low order controller of PID type. Both low frequency performance, mid frequency stability margins and high frequency control activity are taken into account. A detailed investigation shows that a new simple rule for design of anti-aliasing filters gives nearly optimal closed loop performance for a number of representative plant models.