0378927 20240111140818.220120726235959.9 10.1109/ICEEE.2011.6106611 6 s. P cav_un_epca*0378926978-1-4577-1011-71-6Merida CityIEEE2011 High-gain observers integral action microalgae cav_un_auth*0282537 Rodríguez-Mata A. MX cav_un_auth*0282538 Torres-Munoz J. MX cav_un_auth*0282539 Domínguez A.R. MX cav_un_auth*0282540 Hernandez-Villagran D. MX cav_un_auth*0101074 Čelikovský Sergej Teorie řízení Department of Control Theory TŘ TR UTIA-B Department of Control Theory Ústav teorie informace a automatizace AV ČR, v. v. i. textový dokument http://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=19270 284 kB CEZ:AV0Z10750506 This paper deals with the problem of estimating the states in nonlinear systems with parameters that are not precisely knwon through the implementation of proportional nonlinear high gain observers with additional integral action. It is known that non-linear observers (NL-P) show excellent results in the estimation of state variables but these depend heavily on precise knowledge of model parameters, this is not always possible because in many process the parameters may suffer sudden shifts as in the biological processes, which in turn will certainly broke the asymptotical convergence observer property. We propose the addition of a integral action in order to deal with possible change of parameters. In this work it is showed that the so called nonlinear integral high gain observers (NL-PI) are able to cancel the dynamical disturbances due to parameter.changes. We studied the substrate estimation in a wastewater treatment bioreactor. cav_un_auth*0282541 The 8th International Conference on Electrical Engineering, Computing Science and Automatic Control 2011 (CCE 2011) Merida City 26.10.2011-28.10.2011 MX 2013 BC 5 PR http://hdl.handle.net/11104/0210238 2011 textový dokument 284 kB cav_un_epca*0378926 Proceedings of the 2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2011) 978-1-4577-1011-7 1 6 Merida City IEEE 2011 INSPEC Accession Number: 12503263