Practical Process Control for Engineers and Technicians

by Altmann

• ISBN13: 9780750664004
• ISBN10: 0750664002
• Edition: 1st
• Format: Paperback
• Copyright: 2005-05-10
• Publisher: Elsevier Science

Summary

This book is aimed at engineers and technicians who need to have a clear, practical understanding of the essentials of process control, loop tuning and how to optimize the operation of their particular plant or process. The reader would typically be involved in the design, implementation and upgrading of industrial control systems. Mathematical theory has been kept to a minimum with the emphasis throughout on practical applications and useful information. This book will enable the reader to: * Specify and design the loop requirements for a plant using PID control * Identify and apply the essential building blocks in automatic control * Apply the procedures for open and closed loop tuning * Tune control loops with significant dead-times * Demonstrate a clear understanding of analog process control and how to tune analog loops * Explain concepts used by major manufacturers who use the most up-to-date technology in the process control field A practical focus on the optimization of process and plant Readers develop professional competencies, not just theoretical knowledge Reduce dead-time with loop tuning techniques

Table of Contents

Preface	xi
Introduction	1	(17)
Objectives	1	(1)
Introduction	1	(1)
Basic definitions and terms used in process control	2	(1)
Process modeling	2	(3)
Process dynamics and time constants	5	(8)
Types or modes of operation of process control systems	13	(2)
Closed loop controller and process gain calculations	15	(1)
Proportional, integral and derivative control modes	16	(1)
An introduction to cascade control	16	(2)
Process measurement and transducers	18	(34)
Objectives	18	(1)
The definition of transducers and sensors	18	(1)
Listing of common measured variables	18	(1)
The common characteristics of transducers	19	(2)
Sensor dynamics	21	(1)
Selection of sensing devices	21	(1)
Temperature sensors	22	(6)
Pressure transmitters	28	(7)
Flow meters	35	(7)
Level transmitters	42	(2)
The spectrum of user models in measuring transducers	44	(1)
Instrumentation and transducer considerations	45	(3)
Selection criteria and considerations	48	(2)
Introduction to the smart transmitter	50	(2)
Basic principles of control valves and actuators	52	(26)
Objectives	52	(1)
An overview of eight of the most basic types of control valves	52	(15)
Control valve gain, characteristics, distortion and rangeability	67	(4)
Control valve actuators	71	(5)
Control valve positioners	76	(1)
Valve sizing	76	(2)
Fundamentals of control systems	78	(9)
Objectives	78	(1)
On--off control	78	(1)
Modulating control	79	(1)
Open loop control	79	(2)
Closed loop control	81	(3)
Deadtime processes	84	(1)
Process responses	85	(1)
Dead zone	86	(1)
Stability and control modes of closed loops	87	(13)
Objectives	87	(1)
The industrial process in practice	87	(1)
Dynamic behavior of the feed heater	88	(1)
Major disturbances of the feed heater	88	(1)
Stability	89	(1)
Proportional control	90	(3)
Integral control	93	(2)
Derivative control	95	(3)
Proportional, integral and derivative modes	98	(1)
I.S.A. vs `Allen Bradley'	98	(1)
P, I and D relationships and related interactions	98	(1)
Applications of process control modes	99	(1)
Typical PID controller outputs	99	(1)
Digital control principles	100	(8)
Objectives	100	(1)
Digital vs analog: a revision of their definitions	100	(1)
Action in digital control loops	100	(1)
Identifying functions in the frequency domain	101	(2)
The need for digital control	103	(2)
Scanned calculations	105	(1)
Proportional control	105	(1)
Integral control	105	(1)
Derivative control	106	(1)
Lead function as derivative control	106	(1)
Example of incremental form (Siemens S5-100 V)	107	(1)
Real and ideal PID controllers	108	(4)
Objectives	108	(1)
Comparative descriptions of real and ideal controllers	108	(1)
Description of the ideal or the non-interactive PID controller	108	(1)
Description of the real (Interactive) PID controller	109	(1)
Lead function--derivative control with filter	110	(1)
Derivative action and effects of noise	110	(1)
Example of the KENT K90 controllers PID algorithms	111	(1)
Tuning of PID controllers in both open and closed loop control systems	112	(19)
Objectives	112	(1)
Objectives of tuning	112	(2)
Reaction curve method (Ziegler--Nichols)	114	(2)
Ziegler-Nichols open loop tuning method (1)	116	(1)
Ziegler-Nichols open loop method (2) using POI	117	(2)
Loop time constant (LTC) method	119	(1)
Hysteresis problems that may be encountered in open loop tuning	120	(1)
Continuous cycling method (Ziegler--Nichols)	120	(3)
Damped cycling tuning method	123	(3)
Tuning for no overshoot on start-up (Pessen)	126	(1)
Tuning for some overshoot on start-up (Pessen)	127	(1)
Summary of important closed loop tuning algorithms	127	(1)
PID equations: dependent and independent gains	127	(4)
Controller output modes, operating equations and cascade control	131	(11)
Objectives	131	(1)
Controller output	131	(1)
Multiple controller outputs	132	(1)
Saturation and non-saturation of output limits	133	(1)
Cascade control	134	(2)
Initialization of a cascade system	136	(1)
Equations relating to controller configurations	136	(3)
Application notes on the use of equation types	139	(1)
Tuning of a cascade control loop	140	(1)
Cascade control with multiple secondaries	141	(1)
Concepts and applications of feedforward control	142	(5)
Objectives	142	(1)
Application and definition of feedforward control	142	(1)
Manual feedforward control	143	(1)
Automatic feedforward control	143	(1)
Examples of feedforward controllers	144	(1)
Time matching as feedforward control	144	(3)
Combined feedback and feedforward control	147	(3)
Objectives	147	(1)
The feedforward concept	147	(1)
The feedback concept	147	(1)
Combining feedback and feedforward control	148	(1)
Feedback-feedforward summer	148	(1)
Initialization of a combined feedback and feedforward control system	149	(1)
Tuning aspects	149	(1)
Long process deadtime in closed loop control and the Smith Predictor	150	(5)
Objectives	150	(1)
Process deadtime	150	(1)
An example of process deadtime	151	(1)
The Smith Predictor model	152	(1)
The Smith Predictor in theoretical use	153	(1)
The Smith Predictor in reality	153	(1)
An exercise in deadtime compensation	154	(1)
Basic principles of fuzzy logic and neural networks	155	(10)
Objectives	155	(1)
Introduction to fuzzy logic	155	(1)
What is fuzzy logic?	156	(1)
What does fuzzy logic do?	156	(1)
The rules of fuzzy logic	156	(2)
Fuzzy logic example using five rules and patches	158	(1)
The Achilles heel of fuzzy logic	159	(1)
Neural networks	159	(2)
Neural back propagation networking	161	(1)
Training a neuron network	162	(1)
Conclusions and then the next step	163	(2)
Self-tuning intelligent control and statistical process control	165	(11)
Objectives	165	(1)
Self-tuning controllers	165	(1)
Gain scheduling controller	166	(1)
Implementation requirements for self-tuning controllers	167	(1)
Statistical process control (SPC)	167	(1)
Two ways to improve a production process	168	(1)
Obtaining the information required for SPC	169	(4)
Calculating control limits	173	(2)
The logic behind control charts	175	(1)
Appendix A: Some Laplace transform pairs	176	(3)
Appendix B: Block diagram transformation theorems	179	(2)
Appendix C: Detail display	181	(4)
Appendix D: Auxiliary display	185	(3)
Appendix E: Configuring a tuning exercise in a controller	188	(2)
Appendix F: Installation of simulation software	190	(3)
Appendix G: Operation of simulation software	193	(4)
Appendix H: Configuration	197	(1)
Appendix I: General syntax of configuration commands	198	(1)
Appendix J: Configuration commands	199	(9)
Appendix K: Algorithms	208	(15)
Appendix L: Background graphics design	223	(1)
Appendix M: Configuration example	224	(5)
Introduction to exercises	229	(57)
Flow control loop--basic example	231	(3)
Proportional (P) control--flow chart	234	(3)
Integral (I) Control--flow control	237	(3)
Proportional and integral (PI) control--flow control	240	(2)
Introduction to derivative (D) control	242	(4)
Practical introduction into stability aspects	246	(6)
Open loop method--tuning exercise	252	(4)
Closed loop method--tuning exercise	256	(4)
Saturation and non-saturation output limits	260	(3)
Ideal derivative action--ideal PID	263	(4)
Cascade control	267	(4)
Cascade control with one primary and two secondaries	271	(5)
Combined feedback and feedforward control	276	(3)
Deadtime compensation in feedback control	279	(5)
Static value alarm	284	(2)
Index	286