Muutke küpsiste eelistusi

Real Time Control Engineering: Systems And Automation 1st ed. 2016 [Kõva köide]

4.00/5 (2 hinnangut Goodreads-ist)
  • Formaat: Hardback, 181 pages, kõrgus x laius: 235x155 mm, kaal: 553 g, 26 Illustrations, color; 69 Illustrations, black and white; XXIII, 181 p. 95 illus., 26 illus. in color., 1 Hardback
  • Sari: Studies in Systems, Decision and Control 65
  • Ilmumisaeg: 23-Jun-2016
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811015082
  • ISBN-13: 9789811015083
Teised raamatud teemal:
  • Kõva köide
  • Hind: 122,82 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Tavahind: 144,49 €
  • Säästad 15%
  • Raamatu kohalejõudmiseks kirjastusest kulub orienteeruvalt 2-4 nädalat
  • Kogus:
  • Lisa ostukorvi
  • Tasuta tarne
  • Tellimisaeg 2-4 nädalat
  • Lisa soovinimekirja
Real Time Control Engineering: Systems And Automation 1st ed. 2016Suurem pilt
  • Formaat: Hardback, 181 pages, kõrgus x laius: 235x155 mm, kaal: 553 g, 26 Illustrations, color; 69 Illustrations, black and white; XXIII, 181 p. 95 illus., 26 illus. in color., 1 Hardback
  • Sari: Studies in Systems, Decision and Control 65
  • Ilmumisaeg: 23-Jun-2016
  • Kirjastus: Springer Verlag, Singapore
  • ISBN-10: 9811015082
  • ISBN-13: 9789811015083
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789811015083.html
Märksõnad:

This book covers the two broad areas of the electronics and electrical aspects of control applications, highlighting the many different types of control systems of relevance to real-life control system design. The control techniques presented are state-of-the-art. In the electronics section, readers will find essential information on microprocessor, microcontroller, mechatronics and electronics control. The low-level assembly programming language performs basic input/output control techniques as well as controlling the stepper motor and PWM dc motor.

In the electrical section, the book addresses the complete elevator PLC system design, neural network plant control, load flow analysis, and process control, as well as machine vision topics. Illustrative diagrams, circuits and programming examples and algorithms help to explain the details of the system function design. Readers will find a wealth of computer control and industrial automation practices and applications for modern industries, as well as the educational sector.

1 Introduction
1(4)
1.1 Objectives
1(1)
1.2 Highlights of the Book
1(1)
1.3 Organisation of the Book
2(3)
2 Embedded Intruder System
5(22)
2.1 Requirements and Assumptions
6(1)
2.2 Hardware Design
7(7)
2.3 Software Design
14(5)
2.4 System Program
19(8)
3 Mechatronics
27(12)
3.1 Liquid Level Control
27(2)
3.2 Oscillating Planar
29(5)
3.3 Conveyor Inspection Using Shift Registers
34(1)
3.4 Modem Speed Control
35(4)
4 Microcontroller
39(40)
4.1 Basic I/O Modules
39(5)
4.2 LCD and Keypad
44(14)
4.3 Waveform Timings
58(7)
4.4 Pressure Sensing
65(2)
4.5 Temperature Measurement
67(1)
4.6 Stepper Motor Control
67(9)
4.7 Serial Communications
76(3)
5 Electronics Control
79(12)
5.1 Servo Motor Control
79(1)
5.2 Square Wave Generator
80(3)
5.3 PID Controller
83(4)
5.4 Control of an Electro-pneumatic Mechanism
87(4)
6 Electrical System
91(10)
6.1 Elevator Control
91(1)
6.2 Programmable Logic Controller
91(1)
6.3 Ladder Diagram Control Structures
91(7)
6.3.1 Part 1:- Indicating Lights
93(1)
6.3.2 Part 2:- Lift Door Open/Close
94(2)
6.3.3 Part 3:- Lift Up/Down
96(2)
6.4 Safety Control Features
98(3)
7 Power Flow
101(14)
7.1 Power System Analysis
101(1)
7.2 Newton Raphson Formulation
101(3)
7.3 Load Flow Analysis Using Newton Raphson
104(11)
8 Process Control
115(6)
8.1 Water Tank Control System
115(3)
8.1.1 First-Order Derivation
115(3)
8.2 Single Tank Control
118(3)
9 Machine Learning
121(32)
9.1 Neural Network in Process Control
121(1)
9.2 The Artificial Neurons
122(1)
9.3 Techniques Involved in the Controllers
123(1)
9.4 NN Learning Rules
124(2)
9.5 Selection of the Learning Algorithms
126(3)
9.6 The Network Topology
129(1)
9.7 MLP Backpropagation Network for Process Control
130(3)
9.8 Chemical Plant NN Feedback Control System
133(5)
9.8.1 Process Design
134(1)
9.8.2 Process Verification
135(2)
9.8.3 Process Improvement
137(1)
9.9 Remote Operated Neural Network Control Plant
138(4)
9.9.1 Field Instrumentations
138(1)
9.9.2 Scaling and Conversions
139(1)
9.9.3 Control Valves
140(1)
9.9.4 Wireless Transmissions
140(2)
9.10 Valves and Chemical Plant Tunings
142(2)
9.10.1 Desired Chemical Mixture, Samples and NN Data
142(1)
9.10.2 Chemical and Valves Calibration
142(1)
9.10.3 Trial Test in Actual Plant
143(1)
9.11 Computerized Neural Network Control System
144(9)
9.11.1 NN Real Time Control Plant
144(1)
9.11.2 Neural Network Control Valves
145(3)
9.11.3 Intelligent Advisor
148(5)
10 Computer Vision
153(14)
10.1 Image Thresholding
153(1)
10.2 Zhang-Suen Thinning Algorithm
154(1)
10.3 Brief Descriptions of the Program Algorithms
154(7)
10.4 Image Results
161(6)
Appendix A MC68HC11 Registers 167(2)
Appendix B MCU Port Testers 169(4)
Appendix C LCD References 173(4)
References 177(2)
Index 179
Mr Tian Seng Ng holds the MSc degree in computer control and automation. At present, he is a technical staff member at the Nanyang Technological University. He has been working in the field of robotics, control and automation for almost 25 years. His past working experience is in the gantry crane automation system at the wharves, and at the field pumping stations in Singapore. His interest lies in the domain of instrumentations, mechatronics, control systems to machine visions.