Local Model Predictive Control for T-S Fuzzy Systems.

In this paper, a new linear matrix inequality-based model predictive control (MPC) problem is studied for discrete-time nonlinear systems described as Takagi-Sugeno fuzzy systems. A recent local stability approach is applied to improve the performance of the proposed MPC scheme. At each time k , an optimal state-feedback gain that minimizes an objective function is obtained by solving a semidefinite programming problem.

A Multistage Approach for Image Registration.

Successful image registration is an important step for object recognition, target detection, remote sensing, multimodal content fusion, scene blending, and disaster assessment and management. The geometric and photometric variations between images adversely affect the ability for an algorithm to estimate the transformation parameters that relate the two images. Local deformations, lighting conditions, object obstructions, and perspective differences all contribute to the challenges faced by traditional registration techniques.

[Comparison of effect between early and delayed in primary intramedullary nailing combined with locked plate fixation for the treatment of multi-segments tibial fractures of type].

Objective: To compare the clinical results of early and delayed intramedullary nailing and locked plating for the treatment of multi-segments tibial fractures of type AO/ASIF-42C2.

Methods: Between January 2010 and January 2013,45 patients with multi-segments closed tibial fractures of AO/ASIF-42C2 were treated by early primary intramedullary nailing and locked plating in 20 cases as early group and delayed in 25 cases as delayed group. In early group,20 cases included 13 males and 7 females with an average age of (37.

Variable neural adaptive robust control: a switched system approach.

Variable neural adaptive robust control strategies are proposed for the output tracking control of a class of multiinput multioutput uncertain systems. The controllers incorporate a novel variable-structure radial basis function (RBF) network as the self-organizing approximator for unknown system dynamics. It can determine the network structure online dynamically by adding or removing RBFs according to the tracking performance.