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dc.contributor.authorWen, Chenen_US
dc.description.abstractIn this thesis, the review of Iterative Learning Control (ILC) is first introduced, including generic description of ILC, some ILC algorithms and results and connections to other control paradigms. In a separated section, the convergence and robustness, a mainly focused problem in almost every ILC paper, is discussed. Especially, in chapter 3, we review some previous ILC work for nonlinear systems. Following this chapter, from chapter 4 to 7, we present the main contents of this thesis, we propose an iterative learning control method based on the analysis of the constraint to achieve precise tracking control of a class of constrained nonlinear systems over a finite time interval in chapter 4. The learning is done in a feedback configuration formed by the constraint, and the learning law updates the reference input from the plant input of the previous trial. A sufficient condition which guarantees the convergence of the learning is given. From the derivations, we find that the bounds of the asymptotic errors are influenced by the constraint terms and their Lie derivative with respect to (f,G,k).en_US
dc.format.extent109 p.en_US
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Control engineeringen_US
dc.titleIterative learning control for nonlinear systemsen_US
dc.contributor.supervisorSoh, Yeng Chaien_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeMaster of Engineeringen_US
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