The paper presents a new elastic scheduling task model which has been used in the uniprocessor node of a control measuring system. This model allows the selection of a new set of periods for the occurrence of tasks executed in the node of a system in the case when it is necessary to perform additional aperiodic tasks or there is a need to change the time parameters of existing tasks. Selection of periods is performed by heuristic algorithms. This paper presents the results of the experimental use of an elastic scheduling model with a GRASP heuristic algorithm.
Modern control and measurement systems are equipped with interfaces to operate in local area networks and are typically intended to perform complicated data processing and control algorithms. The authors propose a digital system for rapid prototyping of target application devices. The concept solution separates the processing and control section from the hardware interface and user interface section. Both sections constitute independent ARM-based controllers interconnected via a direct USB link. Popular libraries can be used and low-level procedures developed, which enhances the system’s economic viability. A test unit developed for the purpose of the study was built around a SoC ARM7 microsystem and an off-the-shelf palmtop device. It demonstrated a continuous data stream transfer capability up to 150 kB per second, which was sufficient to monitor the performance of an electricity line.
In the last decade of the XX-th century, several academic centers have launched intensive research programs on the brain-computer interface (BCI). The current state of research allows to use certain properties of electromagnetic waves (brain activity) produced by brain neurons, measured using electroencephalographic techniques (EEG recording involves reading from electrodes attached to the scalp - the non-invasive method - or with electrodes implanted directly into the cerebral cortex - the invasive method). A BCI system reads the user's “intentions” by decoding certain features of the EEG signal. Those features are then classified and "translated" (on-line) into commands used to control a computer, prosthesis, wheelchair or other device. In this article, the authors try to show that the BCI is a typical example of a measurement and control unit.