Viúdez Moreiras. DanielMartín Sánchez, Juan M.2025-01-152025-01-152016-07-27Viúdez-Moreiras, D. and Martín-Sánchez J.M. (2016) Guidance System for Control Periods under Modeling Threshold. International Journal of Automation and Control. 10(3), 215-233. 10.1504/IJAAC.2016.077587. https://doi.org/10.1504/IJAAC.2016.0775871740-7516 | eISSN 1740-7524https://doi.org/10.1504/IJAAC.2016.077587https://hdl.handle.net/20.500.14468/25308The registered version of this article, first published in “International Journal of Automation and Control. 10(3), 215-233", is available online at the publisher's website: Inderscience, https://doi.org/10.1504/IJAAC.2016.077587La versión registrada de este artículo, publicado por primera vez en “International Journal of Automation and Control. 10(3), 215-233", está disponible en línea en el sitio web del editor: Inderscience, https://doi.org/10.1504/IJAAC.2016.077587This paper presents a new guidance system for process control that can improve the control performance of model-based advanced controllers or optimised adaptive controllers, when their control periods have to be selected within a lower range of time values that may increase the sensitivity of the predictive model parameters to identification errors. The guidance system generates at each control instant a future desired trajectory for the process output variable under control, from which it computes a set point for the derivative variable of the process output variable. A predictive or adaptive predictive controller drives the derivative variable to its set point and, as a consequence, the process output converges towards said desired trajectory. The new guidance system is illustrated by its application to the level control of a MIMO nonlinear process, in the presence of noises and disturbances. The results show how the control performance of the guidance system is not affected by 'small' control periods that would deteriorate the performance of an adaptive predictive controller for the same application.eninfo:eu-repo/semantics/openAccess33 Ciencias Tecnológicas::3306 Ingeniería y tecnología eléctricasartículooptimised adaptive controlpredictive controladaptive predictive controlderivative controlguidance systemsguidance strategyprocess controlmodelling thresholdmodel-based controlMIMO nonlinear processescontrol performance