The thesis is focused on premature newborn thermomanagement. It is focused particularly on very premature and extremely premature newborns which suffer the highest level of thermolability. The theoretical part deals with the particularities of premature newborn thermoregulation, newborns' reactions to thermal stress, thermomanagement in the delivery room and providing a thermoneutral environment in the incubator. The thesis describes a method of servo-control mode of body temperature, which has not been utilised for premature newborns in Czech Republic. The aim of the thesis is to start using this method and compare it with the method of manual control. Based on the total time not meeting the standard, number of failures and other parameters to assess which method is more suitable for body temperature regulation. The research sample consists of 47 newborsn who were born between the 24th and 32nd gestational week. Quantitative data collection at one-minute intervals was conducted in the 72 hours after birth. The method choice was random. Statistically important differences between the two methods were measured regarding the total time not meeting the standards. The incidence of hyperthemia was higher during manual method, hypothermia when servo-control. Total failure amount was 19%. However, the...

L'objectif de la thèse est de concevoir et développer un système numérique de combinaison de signaux d'horloges hétérogènes (PPS, horloges atomiques, quartz, ...). Le signal résultant possède une meilleure stabilité que chacune des entrée quelque soit la durée d'intégration et il peut détecter des défaillances chez une des entrées. / The goal of the PhD is to design and build a numerical system capable of combining clock signals from various sources (PPS, atomic clocks, quartz, ...). The output signal will have a better stability at each integration time than any single input signal and it could detect failures in input sources.

A robust servo control system based on Integral Variable Structure Model Following Control (IVSMFC) is proposed. The IVSMFC approach comprises a reference model part for specifying the design requirements and an Integral Variable Structure Control (IVSC) part for minimizing the errors between the plant and the model. Sliding mode thus obtained features robustness against external disturbances and parameter variations. Design procedures in both continuous-time and discrete-time have been detailed. The IVSMFC-based servo control system has been successfully applied to a DSP-based brushless DC motor drive for globoidal cam indexing system and to power system. Simulation and experimental results demonstrate that the proposed scheme can achieve fast and robust responses.

This paper explores the problem of electrical sports equipment includes 2D-animation, storage media and the safety-protection over out of control of speed and the supporting supervisory control apparatus. This paper succeeded in developing a highly efficient DSP-based motor driver system in the form of a jogging machine which employs IVSC and RISC control law. The simulation and experimental results show that the proposed system meets the requirements of servo tracking with excellent transient, steady state responses and robustness. This paper design a multi-functional FPGA uses in control system of sports equipment to provide the designing flexibility for different scales, solutions to the difficulties of production and maintenance, and the extension for future development of sports equipment.

In visually guided control of a robot, a large residual problem occurs when the robot configuration is not in the neighborhood of the target acquisition configuration. Most existing uncalibrated visual servoing algorithms use quasi-Gauss-Newton methods which are effective for small residual problems. The solution used in this study switches between a full quasi-Newton method for large residual case and the quasi-Gauss-Newton methods for the small case. Visual servoing to handle large residual problems for tracking a moving target has not previously appeared in the literature. For large residual problems various Hessian approximations are introduced including an approximation of the entire Hessian matrix, the dynamic BFGS (DBFGS) algorithm, and two distinct approximations of the residual term, the modified BFGS (MBFGS) algorithm and the dynamic full Newton method with BFGS (DFN-BFGS) algorithm. Due to the fact that the quasi-Gauss-Newton method has the advantage of fast convergence, the quasi-Gauss-Newton step is used as the iteration is sufficiently near the desired solution. A switching algorithm combines a full quasi-Newton method and a quasi-Gauss-Newton method. Switching occurs if the image error norm is less than the switching criterion, which is heuristically selected. An adaptive forgetting factor called the dynamic adaptive forgetting factor (DAFF) is presented. The DAFF method is a heuristic scheme to determine the forgetting factor value based on the image error norm. Compared to other existing adaptive forgetting factor schemes, the DAFF method yields the best performance for both convergence time and the RMS error. Simulation results verify validity of the proposed switching algorithms with the DAFF method for large residual problems. The switching MBFGS algorithm with the DAFF method significantly improves tracking performance in the presence of noise. This work is the first successfully developed model independent, vision-guided control for large residual with capability to stably track a moving target with a robot.

The Compact Rescue Crawler is a pneumatic legged robot. Two legs of a hexapod were designed and built. The legs are controlled directly from operator inputs. The operator gives foot position inputs through two PHANToM haptic controllers. A PD controller with a supplementary force gain-scheduler control stroke lengths of each cylinder. The force-based position control technique allows the robot feet to track operator inputs to within 10% position error. A guided gait algorithm was developed to allow the operator to control all 6 legs simply by haptically guiding the front two. The operator records successful and collision-free trajectories and the gait coordinator plays the trajectories through the rear legs as they approach the detected obstacles. This hybrid gait algorithm allows the robot to proceed through a hazardous environment, guided by an operator, but without taxing the input capabilities of the human operator.

This thesis presents a new optical imaging technique which measures the structure of objects without the use of lenses. Termed diffraction-contrast imaging (DCI), the method retrieves the object structure from a Fresnel diffraction pattern of the object, using a deconvolution algorithm. DCI is particularly adept at imaging highly transparent objects and this is demonstrated by retrieving the structure of an almost transparent cloud of laser-cooled atoms. Applied to transparent Bose-Einstein condensates, DCI should allow the non-destructive imaging of the condensate while requiring only the minimum possible apparatus of a light source and a detector. (For complete abstract open document)