Rank-one LMI approach to simultaneous stabilization of linear systems

Following a polynomial approach to control design, the simultaneous stabilization by a controller of given fixed order of a family of SISO linear systems is interpreted as an NP-hard BMI feasibility problem. Upon formulating this BMI problem as an LMI problem with an additional non-convex rank constraint, two simultaneous stabilization methods are then proposed. The first method is a heuristic algorithm performing rank minimization by potential reduction. The second method hinges upon necessary conditions and sufficient conditions for simultaneous stabilization derived from geometric properties of the intersection of a set of ellipsoids. Both methods are then illustrated by numerical examples.     

An intelligent IoT with cloud centric medical decision support system for chronic kidney disease prediction

At present days, Internet of Things (IoT) and cloud platforms become widely used in various healthcare applications. The enormous quantity of data produced by the IoT devices in the healthcare sector can be examined on the cloud platform instead of dependent on restricted storage and computation resources exist in the mobile gadgets. For offering effective medicinal services, in this article, an online medical decision support system (OMDSS) is introduced for chronic kidney disease (CKD) prediction. The presented model involves a set of stages namely data gathering, preprocessing, and classification of medical data for the prediction of CKD. For classification, logistic regression (LR) model is applied for classifying the data instances into CKD and non-CKD. In addition, for tuning the parameters of LR, Adaptive Moment Estimation (Adam), and adaptive learning rate optimization algorithm is applied. The performance of the introduced model is examined using a benchmark CKD dataset. The experimental outcome observed the superior characteristics of the presented model on the applied dataset.     

Drag on ensembles of fluid spheres translating in a power-law liquid at moderate Reynolds numbers

This work elucidates the role of power-law rheology on the sedimentation velocity of an ensemble of mono-size spherical Newtonian droplets (free from surfactants) translating in a power-law continuous phase numerically by solving the momentum equations of both phases. A simple sphere-in-sphere cell model has been used to account for inter-drop interactions. In particular, in this study, the effects of the Reynolds number (Re_o), the internal to external fluid characteristic viscosity ratio (k), the volume fraction of the dispersed phase (Φ) and the power-law index of the continuous phase (n_o) on the external flow field, pressure drag (C_dp), friction drag (C_df) and total drag (C_d) coefficients have been analyzed over wide ranges of parameters as follows: 1 ≤ Re_o ≤ 200, 0.1 ≤ k ≤ 50, 0.2 ≤ Φ ≤ 0.6 and 0.6 ≤ n_o ≤ 1.6. Based on the extensive numerical results obtained in this work, a simple predictive correlation has been proposed for the total drag coefficient, which can be used to predict the rate of sedimentation of ensembles of Newtonian fluid spheres in power-law liquids in a new application.     

Joint dynamic probabilistic constraints with projected linear decision rules

We consider multistage stochastic linear optimization problems combining joint dynamic probabilistic constraints with hard constraints. We develop a method for projecting decision rules onto hard constraints of wait-and-see type. We establish the relation between the original (infinite-dimensional) problem and approximating problems working with projections from different subclasses of decision policies. Considering the subclass of linear decision rules and a generalized linear model for the underlying stochastic process with noises that are Gaussian or truncated Gaussian, we show that the value and gradient of the objective and constraint functions of the approximating problems can be computed analytically.     

Instrumental and sensory characterisation of industrially processed applesauces

BACKGROUND: In the context of fruit consumption promotion, applesauce is an interesting ready‐to‐eat product. However, little information has been gathered on its sensory properties. Yet, the processing involved easily triggers rheological and structural changes, possibly modifying these sensory properties. The aim of this study was thus to provide a global approach for applesauce characterisation by studying instrumental and sensory properties, with knowledge of the processing conditions applied. Four applesauce samples processed under controlled parameters were therefore compared with seven purchased applesauces. RESULTS: The four studied samples were characterised by their high creaminess and low graininess. These products were homogeneous and presented a small average particle size (332–354 µm). Their flow properties were best described with the Hershel–Bulkey model. The products were shear‐thinning with low yield stress. Interestingly, significant differences in textural and flow properties were also found among these four manufactured samples. CONCLUSION: Sensory characterisation revealed aromatic and textural diversity even though applesauce is considered as a common product. Differences found among the samples of interest might be related to postharvest maturity of fruits and consequent pectic degradation from cell walls. Finally, the candied odour and flavour that distinguished these products could be related to the extensive heating applied during processing. Copyright © 2009 Society of Chemical Industry     

Performance evaluation of a small scale indirect solar dryer with static reflectors during non-summer months in the Saurashtra region of western India

This paper reports the design and development of an indirect, natural convection batch-type solar dryer fitted with North–South reflectors. With the help of the reflectors the collector efficiency without load was enhanced from 40.0% to 58.5% under peak solar irradiation conditions during a typical day in January in Bhavnagar, Gujarat, India. The corresponding computed values based on heat transfer equations were 36.5% and 50.3%. The desired extent of drying (ca. 12%, wet basis) of ‘papad’ – a popular Indian wafer – could be achieved within 5 h in this static dryer having 1.8 m² area of the collector and computed loading capacity of 3.46 kg. The initial and average values of the drying efficiency were 16.3% and 4.1%, respectively. The drying performance data could be fitted to the diffusivity equation with effective diffusivity value of 3.9 × 10⁻⁹ m² s⁻¹. Despite the high collector efficiency achieved, the average drying efficiency was low on account of under-loading of the dryer, as evident from the increase in drying efficiency to 13% in a smaller dryer loaded with the same amount of wet papad.     

Weighted Sum of Gray Gas Modeling for Nongray Radiation in Combusting Environment Using the Hybrid Solution Methodology

A hybrid solution approach is proposed to solve the radiation transfer equation (RTE) in combusting environment using the weighted sum of gray gases model for modeling the absorption coefficient. The hybrid approach uses a selective combination of the finite-volume method (FVM) and P1 approximation to solve the RTE for different gray gases. A comprehensive study with a wide range of test cases with homogenous and nonhomogenous media is carried out to study the accuracy, speed, and convergence rate of the hybrid solution approach. The differences between hybrid and FVM results are described, and the sources of errors are discussed.     

Rank-one LMIs and Lyapunov's inequality

We describe a new proof of the well-known Lyapunov's matrix inequality about the location of the eigenvalues of a matrix in some region of the complex plane. The proof makes use of standard facts from quadratic and semidefinite programming. Links are established between the Lyapunov matrix, rank-one linear matrix inequalities (LMI), and the Lagrange multiplier arising in duality theory