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This paper addresses the problem of estimating the state for a class of uncertain discrete‐time linear systems with constraints by using an optimization‐based approach. The proposed scheme uses the moving horizon estimation philosophy together with the game theoretical approach to the
filtering to obtain a robust filter with constraint handling. The used approach is constructive since the proposed...
This paper presents a comparison between two state estimation methods for processes with asynchronous and delayed measurements in order to verify which of these techniques is better in terms of dynamic behavior and possibilities of implementation in a real time processor. The methodologies are analyzed through simulations that allow a comparison in a visual form, through error index and with the time...
In this paper the design of state observers or software sensors for a biological process of ethanol production by S. cerevisiae is presented. Two observers (non-linear and sliding) were used for monitoring continuous fermentations. Their performances were evaluated using mathematical model for bioreactor (perfect knowledge of both model structure and parameters. The performance of the observers proposed...
This paper presents a comparative analysis of two nonlinear state estimators applied to the production process of tequila. The estimates consist of an extended Kalman filter (EKF) and a sliding mode observer (SMO), which are assessed to changes in process inputs and model parametric changes. The estimates are used to estimate the microbial growth and production of alcohol from the measurement of glucose...
The aim of this paper is to design and analyze an observer based on high-order sliding mode to estimate states and unknown inputs in a continuous stirred tank reactor (CSTR). Additionally, the designed HOSM allows to reduce the chattering. The performance of HOSM observer is compared with a 1-order sliding mode observer.
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