An LMI approach to constrained optimization with homogeneous forms

This paper considers the problem of determining the minimum Euclidean distance of a point from a polynomial surface in . It is well known that this problem is in general non-convex. The main purpose of the paper is to investigate to what extent linear matrix inequality (LMI) techniques can be exploited for solving this problem. The first result of the paper shows that a lower bound to the global minimum can be achieved via the solution of a one-parameter family of linear matrix inequalities (LMIs). It is also pointed out that for some classes of problems the solution of a single LMI problem provides the lower bound. The second result concerns the tightness of the bound. It is shown that optimality of the lower bound amounts to solving a system of linear equations. An application example is finally presented to show the features of the approach.     

Packet loss detection in networked control systems

One of the main issues related to the reliable operation of network control systems concerns the design of mechanisms able to detect anomalies in the functioning of the communication network through which the control loops are closed. In this article, we address the problem of detecting the occurrence of packet losses and design a mechanism that can detect the occurrence of packet losses directly from process sensor data. Specifically, we propose a moving‐horizon estimation scheme that permits to detect if the packet‐loss rate exceeds prescribed thresholds, which are representative of stability and performance of the control system. We discuss theoretical properties of the proposed solution along with an approximation scheme with reduced computational burden. A numerical example is discussed to substantiate the analysis.     

Feasibility of horizon-switching predictive control under positional and incremental input saturations

This paper proves the validity of a basic feasibility property which makes it possible to extend, to the case of set-point tracking in ANCBI systems under joint positional and incremental input saturations, the approach in [Mosca, E. (2005). Predictive switching supervisory control of persistently disturbed input-saturated plants. Automatica, 41, 55-67] restricted to positional input saturation and the pure regulation problem. An example on the use of the proposed technique is considered.     

Histopathologic changes in human small intestine during storage in Viaspan organ preservation solution

OBJECTIVE: To evaluate the histopathologic changes that occur in human small intestine or time when preserved in Viaspan organ preservation solution. DESIGN: Short segments of human small intestine were placed in standard organ preservation solution (Viaspan) and stored in conditions that mimic the clinical situation associated with clinical organ procurement, preservation, and transplantation. The intestinal segments were removed at sequential time points and placed in 10% formalin. Specimens underwent histopathologic examination to determine time-related changes. SPECIMENS: Short intestinal segments were obtained from seven multiorgan cadaver donors. Specimens were obtained in a way that exactly mimicked small intestinal organ retrieval. RESULTS: Small intestinal histology remained normal for the first 6 hours. After 6 hours, vacuolar separation began to occur between the epithelium and the basement membrane in the upper half of the villi. After 9 hours of cold preservation, epithelial detachment extended deep into the crypts with occasional shedding of cells and villi. CONCLUSIONS: Currently used small intestinal preservation using Viaspan results in considerable histopathologic changes in human jejunum after 9 hours of cold storage. The histopathologic pattern appears normal for the first 6 hours and suggests that preservation times should be limited to this time period when possible.     

Controller design for extending periodic dynamics of a chaotic CO2 laser

The paper considers a single-mode CO₂ laser that exhibits a cascade of period doubling bifurcations leading to chaos when it is driven by a sinusoidal signal of increasing amplitude. The requirement of a proper working of the laser, for relatively large amplitude of the forcing signal, naturally leads to the control problem of stabilizing periodic motions. Two control schemes are designed: the first one is based on delayed control signals for stabilizing unstable periodic orbits embedded in the chaotic attractor, while the second one relies on the cancellation of subharmonic components of the chaotic motions. Simulations and experimental tests are presented to show the control performance.     

Robust strict positive realness: new results for intervalplant-controller families

A frequency domain approach is used to derive several robust strict positive realness results for interval plants and interval plant plus controller families of transfer functions. Based on simple frequency domain properties of transfer functions, the approach provides a framework for obtaining new results and constructing easy proofs of several important existing results on robust strict positive realness. The main new result states that the minimum of the real part of the transfer functions belonging to an interval plant controller family is achieved on one of the 32 Kharitonov segments of the interval plant. The argument used in the proof is of wider interest and suggests easy ways of proving that robustness of other different frequency properties of interval plant plus controller families of transfer functions, such as robust stability of H_∞-norm computation, can be deduced from a fixed number of segments of transfer functions of the family     

The metabolic syndrome and hyper-Lp(a)-lipoproteinemia in peripheral obliterative atherosclerosis: 2 case reports

One of the characteristics of peripheral vascular disease in diabetic patients is that it occurs at the time of detection of diabetes mellitus. As one of the possible pathogenic mechanisms, in non-smokers, is the sol-called metabolic syndrome (obesity, disorders in regard to metabolism of lipids and carbohydrates and hypertension). Lipoprotein Lp(a) is the most atherogenic among lipoproteins. While data on coronary arterial disease exist, although contradictory, there is a small number of those which document the same for peripheral vascular occlusive disease in diabetics. Two patients, non-smokers, with characteristic constellation of risk factors, are described as possible models for further epidemiologic examinations.     

Absolute stability of analytic neural networks: an approach based on finite trajectory length

A neural network (NN) is said to be convergent (or completely stable) when each trajectory tends to an equilibrium point (a stationary state). A stronger property is that of absolute stability, which means that convergence holds for any choice of the neural network parameters, and any choice of the nonlinear functions, within specified and well characterized sets. In particular, the property of absolute stability requires that the NN be convergent also when, for some parameter values, it possesses nonisolated equilibrium points (e.g., a manifold of equilibria). Such a property, which is really well suited for solving several classes of signal processing tasks in real time, cannot be in general established via the classical LaSalle approach, due to its inherent limitations to study convergence in situations where the NN has nonisolated equilibrium points. A method to address absolute stability is developed, based on proving that the total length of the NN trajectories is finite. A fundamental result on absolute stability is given, under the hypothesis that the NN possesses a Lyapunov function, and the nonlinearities involved (neuron activations, inhibitions, etc.) are modeled by analytic functions. At the core of the proof of finiteness of trajectory length is the use of some basic inequalities for analytic functions due to Lojasiewicz. The result is applicable to a large class of neural networks, which includes the networks proposed by Vidyasagar, the Hopfield neural networks, and the standard cellular NN introduced by Chua and Yang.