Continuous-time vs. discrete-time identification models used for adaptive control of nonlinear process

Abstract

An adaptive control is a technique where the controller adopts a structure or parameters somehow to the control conditions and the state of the controlled system. One way how we can fulfil the adaptivity of the controller is a recursive identification of the controlled system which satisfies that parameters of the controller changes according to parameters of the controlled system during the whole control process. The goal of this contribution is to compare identification models that work in continuous and discrete time. The control synthesis uses polynomial approach that satisfies basic control requirements such as a stability, a disturbance attenuation and a reference signal tracking. The control response could be tuned by the choice of the root position in the Pole-placement method. Moreover, this control method could be easily programmable that is big advantage while we use this method in simulation software such as Matlab etc. © ECMS Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose (Editors).