Synergy and Duality of Identification and Control examines the relationship between modelling and control of dynamic systems. Both stochastic and worst-case design approaches are presented. System identification is introducted in worst-case and stochastic frameworks. Interaction between modelling and control is studied at four levels: separate identification and control design, iterative identification and control design, dual control and synergistic interaction of modelling and control. The last part of the book focuses on fast learning control systems via parametric models. This comprehensive monograph is equally suitable for graduate students as well as for researchers in the fields of control engineering and digital signal processing.
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