Digital Control Systems: Volume 1: Fundamentals, Deterministic Control [Paperback]

This well-known book is an introduction to the field of digital, sampled-data control. It treats the field in depth and can be used for courses and for self study. The second edition has been completely revised and expanded with new results. The work now appears in two volumes, with Volume 2 to be published in 1989. The volumes form a unit and take the reader systematically from fundamentals to problems of real applications. The work is directed towards students of electrical and mechanical engineering, computer science (especially with a specialization on automation and control engineering), and other fields like biology, economics, space mathematics and physics. It is also directed to engineers and scientists concerned with solving concrete problems.This well-known book is an introduction to the field of digital, sampled-data control. It treats the field in depth and can be used for courses and for self study. The second edition has been completely revised and expanded with new results. The work now appears in two volumes, with Volume 2 to be published in 1989. The volumes form a unit and take the reader systematically from fundamentals to problems of real applications. The work is directed towards students of electrical and mechanical engineering, computer science (especially with a specialization on automation and control engineering), and other fields like biology, economics, space mathematics and physics. It is also directed to engineers and scientists concerned with solving concrete problems.1 Introduction.- A Fundamentals.- 2 Control with Digital Computers (Process Computers, Microcomputers).- 3 Fundamentals of Linear Sampled-data Systems (Discrete-time Systems).- 3.1 Discrete-time Signals.- 3.1.1 Discrete Functions, Difference Equations.- 3.1.2 Impulse Trains.- 3.1.3 Fourier-Transform of the Impulse Train.- 3.2 Laplace-transformation of Discrete-time Functions and Shannons Sampling Theorem.- 3.2.1 Laplace-transformation.- 3.2.2 Shannons Sampling Theorem.-lĂ#