Multiobjective output-feedback control via LMI optimization

This paper presents an overview of an LMI approach to the multi-objective synthesis of linear output-feedback controllers. The design objectives can be a mix of H1 performance, H 2 performance, passivity, asymptotic disturbance rejection, time-domain constraints, and constraints on the closed-loop pole location. In addition, these objectives can be specified on different channels of the closed-loop system. When all objectives are formulated in terms of a common Lyapunov function, controller design amounts to solving a system of linear matrix inequalities. The validity of this approach is illustrated by a realistic design example. 1 Introduction Linear matrix inequalities (LMIs) have emerged as a powerful formulation and design technique for a variety of linear control problems [9]. Since solving LMIs is a convex optimization problem, such formulations offer numerically tractable means of attacking problems that lack analytical solution. In addition, efficient interior-point algorithms..

GLAND AND ZONAL SEGMENTATION OF PROSTATE ON T2W MR IMAGES

International audienceFor many years, prostate segmentation on MR images concerned only the extraction of the entire gland. Currently, in the focal treatment era, there is a continuously increasing need for the separation of the different parts of the organ. In this paper, we propose an automatic segmentation method based on the use of T2W images and atlas images to segment the prostate and to isolate the peripheral and transition zones. The algorithm consists of two stages. First, the target image is registered with each zonal atlas image then the segmentation is obtained by the application of an evidential C-Means clustering. The method was evaluated on a representative and multi-centric image base and yielded mean Dice accuracy values of 0.81, 0.70, and 0.62 for the prostate, the transition zone, and peripheral zone, respectively