Logo

Electromechanisms: Automatic Controls

Large book cover: Electromechanisms: Automatic Controls

Electromechanisms: Automatic Controls
by

Publisher: Delmar Publishers
ISBN/ASIN: B0006C0T4E
Number of pages: 215

Description:
These materials are intended to provide a meaningful experience with automatic controls for students of modern technology. The topics included provide exposure to basic principles of control systems, transducers, actuators, amplifiers, and controllers.

Home page url

Download or read it online for free here:
Download link
(multiple formats)

Similar books

Book cover: Discrete Time SystemsDiscrete Time Systems
by - InTech
This book covers the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications.
(7831 views)
Book cover: Lectures on Stochastic Control and Nonlinear FilteringLectures on Stochastic Control and Nonlinear Filtering
by - Tata Institute of Fundamental Research
There are actually two separate series of lectures, on controlled stochastic jump processes and nonlinear filtering respectively. They are united however, by the common philosophy of treating Markov processes by methods of stochastic calculus.
(5116 views)
Book cover: Advanced Model Predictive ControlAdvanced Model Predictive Control
by - InTech
Model Predictive Control refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request to complicated process plants, MPC has been accepted in many practical fields.
(7174 views)
Book cover: Discrete-Event Control of Stochastic Networks: Multimodularity and RegularityDiscrete-Event Control of Stochastic Networks: Multimodularity and Regularity
by - Springer
Opening new directions in research in stochastic control, this book focuses on a wide class of control and of optimization problems over sequences of integer numbers. The theory is applied to the control of stochastic discrete-event dynamic systems.
(5017 views)