In natural sciences, especially in life sciences, controller designers frequently meet the problem that though the controlled system is modeled by a set of nonlinearly coupled Ordinary Differential Equations (ODE) containing various independent variables, only a single control input is available by the use of which the propagation of only one variable has to be controlled. Normally the controlled state variable can be observed by direct measurements, while no sensors are available for obtaining information on the propagation of the other ones. Though in the possession of a reliable system model one has good odds to develop state observers, in the practice just the reliable model used to be missing. While the traditional control design methodologies normally need some state estimation, the Fixed Point Iteration-based (FPI) Adaptive Controller was developed to evade this difficulty. In this design instead modeling the effects of the propagation of the various state variables, these effects are directly observed and compensated on this basis. This approach can be used without structural modification if certain effects appear through some time-delay (Delayed Differential Equations - DDE). In many cases simple and effective models can be developed that contain only pure delay effects. In this paper it is shown that a recent DDE model of Diabetes Mellitus can be used in the FPI-based adaptive blood glucose concentration level control even if the available model is very imprecise. This statement is substantiated by numerical simulations.

Ultra-wideband (UWB) radars which are mainly focused on contactless detection of breath, heartbeat and other biological signals are generally referred to as biometric radars. It is expecting that these radars will find a whole range of applications from the medical field, through supporting emergency situation solution, up to monitoring people in their dwelling (e.g. ambient assisted living programs). Motivated by promising applications of biometric radars, we will focus in this paper on contactless measurement of breathing frequency and heart rate of static persons by UWB radar. At first, the algorithm for the estimation of the breathing frequency of a person will be outlined. Then, the main emphasis will be placed on the development of an efficient approach for the heart rate estimation. The proposed solution will include radar signal processing procedure for static person ranging, methods for improvement of low-level echo of target-to-clutter and noise ratio (exponential averaging, low-pass filter, Savitzky-Golay filter and single delay line canceller), and finally the heart rate estimation itself (peak-to-average power ratio, Welch periodogram). The good performance of the proposed algorithms will be illustrated by experimental results.

In the past period, great efforts have been made to develop methods for people detection based on monitoring their respiratory motion using ultra-wide band sensors (radars). The basic principle of these methods consists in the detection of signal components of raw radar data possessing a significant power in the frequency band 0.1 Hz-0.7 Hz (a frequency range of human respiratory rate) for a constant range between the target and radar antennas. In the connection with the localization of people, a new requirement has been appeared. It has been requested not only to localize people, but also to estimate the frequency of their breathing. This finding may indicate health and psychological state of monitored persons. However, the problem of multiple persons localization associated with the estimation of their breathing rate has not been yet studied deeply. In order to fill this gap, a new radar signal processing procedure for a joint localization and breathing rate estimation of persons will be introduced in the paper. The performance of the proposed procedure will be illustrated by an experimental scenario intent on through-the-wall localization and respiratory rate estimation of two static persons using single ultra-wide band sensor employing one transmitting and two receiving antennas.

Autonomous robots are intelligent machines capable of performing tasks by themselves, without explicit human control. They can find quit a number of unique applications. Here, their utilisation for surveillance, monitoring and reconnaissance in hostile and dangerous to life environment intent on human being detection and/or static object imaging is up-to-date, promising and challenging as well. The fruitfulness of this application of robot systems is determined by many factors. The effective and reliable sensor system for human being detection and localization and static object imaging under wide variety of scenarios can be rated among them. In the last decade, it has been shown that ultra-wideband (UWB) radars (sensors) can be used with advantage as day and night, and under all-weather conditions sensors for person localization and static object imaging. Taking into account this fact, this paper will be intent on the analyses of UWB sensor applicability as the part of the smart sensor systems of robots to be used at emergency situation solutions. Summarizing the results of theoretical analyses and experiments with UWB sensors presented in the paper, it will be concluded that the short-range UWB radars have the great potential to be used as a standard equipment of surveillance and reconnaissance robot systems of future.