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This article provides a comparative analysis of two common control configurations used to control the side-stream distillation used to separate benzene, toluene and xylene as suggested by Doukas and Lyben. Their under-actuated model has been considered as the model of distillation column and the internal model controller is designed considering a Singular Value Decomposition (SVD) and Virtual Inputs (VI) techniques. An internal controller design based on VI is proposed in this article for this kind of underactuated systems. This design is used to control in parallel the distillation process and its model in real time. The proposed controller design is simple and systematic in relation with the desired closed loop specifications of the internal model control structure. Furthermore, the controller obtained ensure robustness to process variations. The SVD technique can realize the decoupling of under-actuated processes and wipe out unrealizable factors by introducing compensation terms, affecting the dynamic of the system. The aim of this article is to make a comparison between our proposed VI controller and the SVD approach. The results we obtained confirmed the potentials of the proposed controller based on VI considering the set point tracking and its robustness.

This paper deals with the issue of stochastic admissibility and robust extended dissipative control for uncertain delayed hybrid descriptor systems (DHDSs) under a unified framework. Belonging to a convex bounded domain, the parameter uncertainties are time-invariant and appear in the state matrix, input matrix and disturbance matrix. Firstly, a stochastic Lyapunov–Krasovskii functional is proposed to reflect the information of time-varying delays and Markovian jump modes, and singular value decomposition technique is utilized to derive novel criteria that ensure the stochastic admissibility and robust extended dissipativity of DHDSs. Then, under a unified framework, the desired robustly stabilizing state feedback controller is realized in terms of linear matrix inequalities. Finally, two examples including a numerical example and an oil catalytic cracking process are applied to corroborate the effectiveness of the derived synthesis scheme. [ABSTRACT FROM AUTHOR]

Downscaling techniques are required to describe the linkages between Global Climate Model outputs at coarse-grid resolutions to surface hydrologic variables at relevant finer scales for climate change impact and adaptation studies. In particular, several statistical methods have been proposed in many previous studies for downscaling of extreme temperature series for a single local site without taking into account the observed spatial dependence of these series between different locations. The present study proposes therefore an improved statistical approach to downscaling of daily maximum (Tmax) and minimum (Tmin) temperature series located at many different sites concurrently. This new multisite multivariate statistical downscaling (MMSD) method was based on a combination of the modeling of the linkages between local daily temperature extremes and global climate predictors by a multiple linear regression model; and the modeling of its stochastic components by the combined singular value decomposition and multivariate autoregressive (SVD-MAR) model to represent more effectively and more accurately the space-time variabilities of these extreme daily temperature series. Results of an illustrative application using daily extreme temperature data from a network of four weather stations in Bangladesh and two different NCEP/NCAR reanalysis datasets have indicated the effectiveness and accuracy of the proposed approach. In particular, this new approach was found to be able to reproduce accurately the basic statistical properties of the Tmax and Tmin at a single site as well as the spatial variability of temperature extremes between different locations. In addition, it has been demonstrated that the proposed method can produce better results than those given by the widely-used single-site downscaling SDSM procedure, especially in preserving the observed inter-site correlations. [ABSTRACT FROM AUTHOR]

This article provides a comparative analysis of two common control configurations used to control the side-stream distillation used to separate benzene, toluene and xylene as suggested by Doukas and Lyben. Their under-actuated model has been considered as the model of distillation column and the internal model controller is designed considering a Singular Value Decomposition (SVD) and Virtual Inputs (VI) techniques. An internal controller design based on VI is proposed in this article for this kind of underactuated systems. This design is used to control in parallel the distillation process and its model in real time. The proposed controller design is simple and systematic in relation with the desired closed loop specifications of the internal model control structure. Furthermore, the controller obtained ensure robustness to process variations. The SVD technique can realize the decoupling of under-actuated processes and wipe out unrealizable factors by introducing compensation terms, affecting the dynamic of the system. The aim of this article is to make a comparison between our proposed VI controller and the SVD approach. The results we obtained confirmed the potentials of the proposed controller based on VI considering the set point tracking and its robustness. [ABSTRACT FROM AUTHOR]

Proposing a comprehensive model to predict the fatigue life of composite structures under dynamic loading has always been a challenging problem. In this study, an attempt has been made to develop a polynomial model by utilization of experimental data together with singular value decomposition technique to estimate the fatigue life of composite materials. The model is based on a nonlinear mathematical function with effective parameters related to fatigue phenomenon in a nondimensional form. For this, four effective parameters such as cyclic stress amplitude, static strength, stress ratio, and fiber angle have been considered in modeling process. To evaluate the capability of this model a comparison has been made with some available experimental results where a good agreement is achieved. So, the obtained results demonstrate that despite system complexity and inability to extract an analytical model for estimating the fatigue life of composite materials, singular value decomposition method could be known as a useful and powerful tool for modeling. [ABSTRACT FROM AUTHOR]

The authors address the problem of support recovery with multiple measurement vectors (MMV) in this study. The scale of an MMV is reduced by using the singular value decomposition technique, and a novel l2 –l1 minimisation model with two variables for the reduced MMV is proposed. Then a new alternating minimisation algorithm based on the alternating direction method of multipliers is presented. They prove the globally convergence property of the presented algorithm. Several numerical simulations both on random data and for direction‐of‐arrival estimation are conducted to evaluate the performance of the proposed method for support recovery of MMV. [ABSTRACT FROM AUTHOR]