Switching-iterative learning control method for discrete-time switching system



In this paper, we propose a new monotonically convergent switching iterative learning control for a class of linear discrete time switched system. It is assumed that the considered switched systems are operated during a finite time interval repetitively, and then the iterative learning control scheme can be introduced. After the switched system is transformed into a 2D repetitive system, sufficient conditions in terms of linear matrix inequalities (LMIs) are derived by using a Lyapunov functional approach and a quadratic performance function. It is shown that if certain LMIs are met, the tracking error \(l_2\) norm converges monotonically to zero between (subsystem/iteration), while the switching learning gains could be determined directly by solving the LMIs.The integrated design of this SILC scheme is transformed into a robust monotonic stabilizability problem (RMS) of an uncertain switched system. A numerical simulation example is established shown the effectiveness of the proposed method .


Switched systems Iterative learning control (ILC) Quadratic function \(l_2 \) norm Tracking control Polytopic uncertainties Linear matrix inequality 


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© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Laboratory of Analysis and Control and conception of Systems (LACCS), National Engineering School of TunisUniversity of Tunis El ManarTunisTunisia

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