New Control Systems and Electronics Engineering Sections Published at Sciences Social Network
Mannheim, Germany (PRWEB) December 11, 2012
ScienceIndex.com is a Control Systems Engineering and Electronics Engineering Sciences Social Network established in 1998 to index the very latest news, headlines, references and resources from science journals, books and websites worldwide. The site covers news in all fields of biology, business, chemistry, engineering, geography, health, mathematics and society. In the field of Engineering Sciences, the site has now included the two new categories Control Systems Engineering and Electronics Engineering. While the Control Systems Engineering section covers systems in which outputs are forced to change in a desired manner during time, the Electronics Engineering section covers manipulation of voltages and electric currents by using devices.
ScienceIndex.com’s Engineering Technology Category covers the design, manufacture, and operation of efficient and economical structures, machines, processes, and systems. Its eight sections include Architecture, Chemical Engineering, Civil Engineering, Communication, Control Systems, Electronics, Industrial Engineering, and Mechanical Engineering. Users can receive alerts for newly published content in this category by subscribing to ScienceIndex.com’s Engineering Technology Category RSS feed.
ScienceIndex.com’s Control Systems Engineering section covers systems in which outputs are forced to change in a desired manner during time. It currently contains 5,330 articles partly derived from 40 scientific Control Systems Engineering journals. The latest articles in this category are also available through a Control Systems Engineering Section RSS feed. One of the latest additions to this section presents a general stability criterion for switched linear systems havingstable and unstable subsystems. The authors report conditions on a switching signal that guarantee that solutions of a switched linear system converge asymptotically to zero. These conditions apply to continuous, discrete-time and hybrid switched linear systems, those having both stable subsystems and mixtures of stable and unstable subsystems. Another recently included article presents a noise covariance estimation for Kalman filter tuning using Bayesian approach and Monte Carlo. The authors tested performance of the approach on various systems and noise properties and compare the speed of convergence with the Cram