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Guaranteeing stability of control applications in embedded systems, or cyber-physical systems, is perhaps the alpha and omega of implementing such applications. However, as opposed to the classical real-time systems where often the acceptance criterion is meeting the deadline, control applications do not primarily enforce hard deadlines. In the case of control applications, stability is considered

Time-triggered periodic control implementations are over provisioned for many execution scenarios in which the states of the controlled plants are close to equilibrium. To address this inefficient use of computation resources, researchers have proposed self-triggered control approaches in which the control task computes its execution deadline at runtime based on the state and dynamical properties

The problem to minimize power losses in an electrical network subject to voltage and power constraints is in general hard to solve. However, it has recently been discovered that semidefinite programming relaxations in many cases enable exact computation of the global optimum. Here we point out a fundamental reason for the successful relaxations, namely that the passive network components give rise

A correct design of controllers must necessarily account for the schedule of the controller task over the processor. Existing design techniques are based on the assumption that there is no delay, or the delay is constant over time. However, in practice, almost all controllers have time-varying delay, hence invalidating this assumption. In this paper, we introduce a period design policy, in which t

Joint wheel-slip and vehicle-motion estimation is considered, based on measurements from wheel encoders, an inertial measurement unit, and a global positioning system (GPS). The proposed strategy effectively employs the Rao-Blackwellized particle-filtering framework using a kinematic model. Key vari- ables in active safety systems, such as longitudinal velocity, roll angle, and wheel slip for all

We present a framework for the solution of control and estimation problems under a signal-to-noise (SNR) ratio constraint. The framework can be used to design optimal linear controllers, based on output feedback, with two degrees of freedom: One part of the controller is placed before the communication channel and represents sensing and encoding operations. The other part represents decoding and i

In neuroscience a number of new techniques have been developed by means of which it has become possible to study the activity of the living human brain. By means of these techniques we are beginning to understand the neurophysiology behind environmental attitudes and preferences. In addition to an introduction to cognitive neuroscience, this invited symposium contains a number of presentations, wh