Approximate and sampled-data predictors for control of nonlinear delay systems |
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| Affiliation: | 1. Department of Mathematics, National Technical University of Athens, Zografou Campus, 15780 Athens, Greece;2. Department of Mechanical and Aerospace Engineering, University of California, San Diego, La Jolla, CA 92093-0411, USA\n;1. Department of Computer Science and Mathematics, University of Passau, Dr-Hans-Kapfinger Strasse, 12, R.109, Passau, 94032, Germany;2. Insight Centre for Data Analytics, National University of Ireland, Insight, IDA Buisiness Park, Lower Dangan, Galway, Ireland;3. Computer Science Department, Federal University of Rio de Janeiro, Caixa-Postal 68530, CEP: 21941-916, Rio de Janeiro, RJ, Brazil;4. College of Graduate Studies, University of South Africa, Pretoria, South Africa |
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| Abstract: | This tutorial research article presents all recent advances on the use of approximate and sampled-data predictors for time-delay systems. The implementation of predictor feedback for delay systems requires the so-called predictor mapping, i.e., the prediction of the future value of the state vector. However, predictor mappings are rarely available for nonlinear systems. The approximate predictors allow us to overcome this challenge and implement predictor feedback safely for nonlinear time-delay systems even in the case of sampled measurements. The present article reviews the implementation schemes for predictor feedback and provides illustrative examples, which can help the reader to understand the importance of the topic. |
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