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In this contribution, an efficient Real-time Optimization (RTO) scheme for the optimal operation of chemical processes under uncertainty is proposed. This work builds on two recently published iterative robust optimization methodologies: Modifier Adaptation with Quadratic Approximation (MAWQA) and Directional Modifier Adaptation (DMA) and proposes a unified framework where the benefits of both methods...
The research is relevant since there is a necessity to solve identification problems of non-stationary signals of control and communication systems in conditions of uncertainty. Research objective is the development of models and algorithms of non-stationary signal identification with variables, time-dependent parameters and with account of additional a-priory information. Integrated system of mathematical...
Robust fault detection based on envelopes generated using a parameter bounded model has been studied from several approaches. But none of the existing approaches can produce the exact system envelopes without increasing the uncertainty over the system states, or at least, approximate envelopes controlling the degree of uncertainty added by the envelope generation algorithm. This paper presents a new...
Generating signals with a prespecified autocorrelation, available from some input design, while satisfying constraints on input and output signals of the systems which the signal is to be applied on is an important problem in system identification. This paper extends a recently proposed method for such signal generation. The method is modified to be robust to uncertainties in the system model. An...
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