In a recent paper the authors proposed a new frequency-domain approach to identify poles in discrete-time linear systems. The discrete rational transfer function is represented in a rational Laguerre-basis, where the basis elements are expressed by powers of the Blaschke-function. This function can be interpreted as a congruence transform on the Poincare unit disc model of the hyperbolic geometry. The identification of a pole is given as a hyperbolic transform of the limit of a quotient-sequence formed from the Laguerre-Fourier coefficients. This paper extends this approach for using discrete time-domain data directly.

 This paper presents the FPGA (Field Programmable Gate Array) implementation of tracking algorithms based on the estimation of a moving target status in space. Two Bayesian estimators, Kalman Filter (KF) and Extended Kalman Filter (EKF), are used to track the targets with several interacting models. Hardware architectures have been proposed for different cases. The targeted circuit was an XC2v1000 FPGA embedded on the Celoxica RC200 board. A tool was designed with visual C++ to generate automatically FPGA configurations, through the use of Handel-C language. This work was completed with an experimental validation which consists in the real-time tracking of sinusoidal signal.

 A nonlinear operator based approach to robust estimation is introduced for discrete-time systems. It involves a signal entering a communications channel with nonlinearities, transport delay and uncertainties. The measurements are assumed to be corrupted by coloured noise which is correlated with the signal to be estimated. The signal and noise model parameters are assumed to be subject to perturbations represented by random variables with known means and covariances. The theoretical solution does not involve linearization or approximations. In the limiting case of a linear system the estimator has the form of a Wiener filter in discrete-time polynomial matrix system form.

 This paper presents a hands-on course in networked control systems (NCS) to be integrated in the education of embedded control systems engineers. The course activities have a strong practical component and most of them are applied exercises to be implemented in a NCS setup. The paper describes the experimental setup and then proposes several activities that can be shaped into a course program according to the needs and diverse background of the targeted audience.

 Real permanent magnet synchronous machines often suffer from significant deviations from ideal ones. They usually occur as the result of simplified and cost-effective manufacturing, but they are also the source of performance degradation. The main problem is the torque-ripple, which is inadmissible in most of the applications. This paper analyses the main sources of this torque-ripple and presents a method to compensate it. The technique used is based on measurements and off-line calculations, followed by real-time control algorithms. The effectiveness of the method is demonstrated on an experimental setup.

 Unfalsified control is applied to an experimental inverted pendulum in the lab. A non-linear model for the system is developed. Using a set of six candidate controllers, of which two are destabilizing, a supervisory program is built. Experimental results show the best controllers are selected most of the time. When a destabilizing controller is put in the loop it is quickly removed and the performance does not degrade significantly. The application shows unfalsified control can be useful for control adaptation to process changes, even knowing it can some times select destabilizing controllers.