Eksteen, Johannes Jacobus ArnoldiHeyns, P.S. (Philippus Stephanus)2017-05-102016-05J. J. A. Eksteen & P. S. Heyns (2016) An alternative update formula for nonlinear model-based iterative learning control, Inverse Problems in Science and Engineering, 24:5, 860-888, DOI: 10.1080/17415977.2015.1088536.1741-5977 (print)1741-5985 (online)10.1080/17415977.2015.1088536http://hdl.handle.net/2263/60308The conventional iterative learning control (ILC) algorithm for modelbased ILC of non-linear systems is presented with the use of a nonlinear inverse model as ILC compensator. The non-linear inverse model is solved with stable inversion. In addition, an alternative ILC algorithm for model-based ILC of non-linear systems is developed, also with using a non-linear inverse model as ILC compensator. Some connections between the conventional and alternative ILC algorithms and Picard, Mann and Ishikawa iterations are explored. The conventional and alternative algorithms are compared in a number of theoretical examples.en© 2015 Taylor and Francis. This is an electronic version of an article published in Inverse Problems in Science and Engineering, vol. 24, no. 5, pp. 860-888, 2016. doi :10.1080/17415977.2015.1088536. Inverse Problems in Science and Engineering is available online at : http://www.tandfonline.com/loi/gipe20.Stable inversionPicard iterationMann iterationResponse reconstructionFatigue testingDiscrete timeNon-linearIterative learning control (ILC)Engineering, built environment and information technology articles SDG-09SDG-09: Industry, innovation and infrastructureEngineering, built environment and information technology articles SDG-12SDG-12: Responsible consumption and productionPostprint Article