Kategoria BISAC: Science >> System Theory

Combining research approaches from biology, philosophy and linguistics, the field of Biosemiotics proposes that animals, plants and single cells all engage in semiosis the conversion of objective signals into conventional signs. This has important implications and applications for issues ranging from natural selection to animal behavior and human psychology, leaving biosemiotics at the cutting edge of the research on the fundamentals of life.

Drawing on an international expertise, the book details the history and study of biosemiotics, and provides a state-of-the-art summary of the...

While conceptually elegant, the generic formulations of nonlinear model predictive control are not ready to use for the stabilization of relatively fast systems. Doctor Alamir presents a successful approach to this problem based on a co-operation between structural considerations and on-line optimization. The balance between structural and optimization aspects of the method is dependent on the system being considered so the many examples developed here aim to transmit a mode of thought rather than a ready-to-use recipe. Among the systems given detailed treatment are:

• double...

Many important physical systems have input-output properties related to the conservation, dissipation and transport of energy. The theory surrounding such "dissipative properties" may be used as a framework for the design and analysis of control systems. The consideration of dissipativity is useful and may be indispensable for control applications like robotics, active vibration damping and circuit theory and for some control techniques themselves: adaptive, nonlinear-H-infinity, and inverse-optimal control among them.

Dissipative Systems Analysis and Control...

This monograph studies the design of robust, monotonically-convergent iterative learning controllers for discrete-time systems. It presents a unified analysis and design framework that enables designers to consider both robustness and monotonic convergence for typical uncertainty models, including parametric interval uncertainties, iteration-domain frequency uncertainty, and iteration-domain stochastic uncertainty. The book shows how to use robust iterative learning control in the face of model uncertainty.