Abstract
An iterative controller design scheme is presented which takes into account the inter-dependence of the modeling and controller design problems. This iterative scheme consists of closed-loop identification and controller redesign cycles. In each cycle, the plant model is identified in a closed-loop using the controller designed in the previous cycle. Then a new controller is redesigned by using the identified model. The iterative process continues until convergence. The q-Markov cover algorithm obtains system state-space models which have the same first q-Markov parameters and covariance parameters as the physical system generating the input-output data. At convergence the controller and the plant model are considered to be consistent. >
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