Anisotropy-based performance analysis of linear discrete time invariant control systems

The anisotropic norm of a linear discrete-time-invariant system measures system output sensitivity to stationary Gaussian input disturbances of bounded mean anisotropy. Mean anisotropy characterizes the degree of predictability (or colouredness) and spatial non-roundness of the noise. The anisotropic norm falls between the H-2 and H-infinity norms and accommodates their loss of performance when the probability structure of input disturbances is not exactly known. This paper develops a method for numerical computation of the anisotropic norm which involves linked Riccati and Lyapunov equations and an associated special type equation.

On the Hopf bifurcation in control systems with a bounded nonlinearity asymptotically homogeneous at infinity

The paper studies existence, uniqueness, and stability of large-amplitude periodic cycles arising in Hopf bifurcation at infinity of autonomous control systems with bounded nonlinear feedback. We consider systems with functional nonlinearities of Landesman-Lazer type and a class of systems with hysteresis nonlinearities. The method is based on the technique of parameter functionalization and methods of monotone concave and convex operators. (C) 2001 Academic Press.

Differential inclusions and robust control theory

Uncontrolled systems (x) over dot is an element of Ax, where A is a non-empty compact set of matrices, and controlled systems (x) over dot is an element of Ax + Bu are considered. Higher-order systems 0 is an element of Px - Du, where and are sets of differential polynomials, are also studied. It is shown that, under natural conditions commonly occurring in robust control theory, with some mild additional restrictions, asymptotic stability of differential inclusions is guaranteed. The main results are variants of small-gain theorems and the principal technique used is the Krasnosel'skii-Pokrovskii principle of absence of bounded solutions.

Body size and ovarian cancer: case-control study and systematic review (Australia)

Objective: Although increased body mass is an established risk factor for a variety of cancers, its relation with cancer of the ovary is unclear. We therefore investigated the association between measures of body mass index (BMI) and ovarian cancer risk. Methods: Data from an Australian case-control study of 775 ovarian cancer cases and 846 controls were used to examine the association with BMI. We have also summarized the results from a number of other studies that have examined this association. Results: There was a significant increased risk of ovarian cancer with increasing BMI, with women in the top 15% of the BMI range having an odds ratio (OR) of 1.9 (95% confidence interval (CI), 1.3-2.6) compared with those in the middle 30%. Stratifying by physical activity showed a stronger effect among inactive women (OR = 3.0, 95% CI 1.3-6.9). The overall effect was consistent with the findings of most prior population-based case-control studies, while cohort studies reported positive effects closer to the null. Hospital-based studies gave variable results. Conclusions: Taken together, the evidence is in favor of a small to moderate positive relation between high BMI and occurrence of ovarian cancer.