Control engg

1. Chapter 1 THE EXCITEMENT OF CONTROL ENGINEERING
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2. This chapter is intended to provide motivation for studying control engineering.
3. In particular it covers: • an overview of the scope of control • historical periods in the development of control theory • types of control problems • introduction to system integration • economic benefits analysis 1.2 Motivation for Control Engineering Feedback control has a long history which began with the early desire of humans to harness the materials and forces of nature to their advantage.
4. Early examples of control devices include clock regulating systems and mechanisms for keeping wind-mills pointed into the wind.
5. A key step forward in the development of control occurred during the industrial revolution.
6. At that time, machines were developed which greatly enhanced the capacity to turn raw materials into products of benefit to society.
7. However, the associated machines, specifically steam engines, involved large amounts of power and it was soon realized that this power needed to be controlled in an organized fashion if the systems were to operate safely and efficiently.
8. A major development at this time was Watt’s fly ball governor.
9. This device regulated the speed of a steam engine by throttling the flow of steam, see Figure 1.1.
10. These devices remain in service to this day.
11. 5 6 The Excitement of Control Engineering Chapter 1 Figure 1.1.
12. Watt’s fly ball governor The World Wars also lead to many developments in control engineering.
13. Some of these were associated with guidance systems whilst others were connected with the enhanced manufacturing requirements necessitated by the war effort.
14. The push into space in the 1960’s and 70’s also depended on control developments.
15. These developments then flowed back into consumer goods, as well as commercial, environmental and medical applications.
16. These applications of advanced control have continued at a rapid pace.
17. To quote just one example from the author’s direct experience, centre line thickness control in rolling mills has been a major success story for the application of advanced control ideas.
18. Indeed, the accuracy of centre line thickness control has improved by two orders of magnitude over the past 50 years due, in part, to enhanced control.
19. For many companies these developments were not only central to increased profitability but also to remaining in business.
20. By the end of the twentieth century, control has become a ubiquitous (but largely unseen) element of modern society.
21. Virtually every system we come in contact with is underpinned by sophisticated control systems.
22. Examples range from simple household products (temperature regulation in air-conditioners, thermostats in hot water heaters etc.) to more sophisticated systems such as the family car (which has hundreds of control loops) to large scale systems (such as chemical plants, aircraft, and manufacturing processes).
23. For example, Figure 1.2 on page 8 shows the process schematic of a Kellogg ammonia plant.
24. There are about 400 of these plants around the world.
25. An integrated chemical plant, of the type shown in Figure 1.2 will typically have many hundreds of control loops.
26. Indeed, for simplicity, we have not shown many of the utilities in Figure 1.2, yet these also have substantial numbers of control loops associated with them.
27. Many of these industrial controllers involve cutting edge technologies.
28. For example, in the case of rolling mills (illustrated in Figure 1.
29. 3 on page 13), the control system involves forces of the order of 2,000 tonnes, speeds up to 120 km/hour and tolerances (in the aluminum industry) of 5 micrometers or 1/500th of the thickness of a human hair! All of this is achieved with precision hardware, advanced computational tools and sophisticated control algorithms.
30. Beyond these industrial examples, feedback regulatory mechanisms are central to the operation of biological systems, communication networks, national economies, and even human interactions.
31. Indeed if one thinks carefully, control in one form or another, can be found in every aspect of life.
32. In this context, control engineering is concerned with designing, implementing and maintaining these systems.
33. As we shall see later, this is one of the most challenging and interesting areas of modern engineering.
34. Indeed, to carry out control successfully one needs to combine many disciplines including modeling (to capture the underlying physics and chemistry of the process), sensor technology (to measure the status of the system), actuators (to apply corrective action to the system), communications (to transmit data), computing (to perform the complex task of changing measured data into appropriate actuator actions), and interfacing (to allow the multitude of different components in a control system to talk to each other in a seemless fashion).
35. Thus control engineering is an exciting multidisciplinary subject with an enormously large range of practical applications.
36. Moreover, interest in control is unlikely to diminish in the foreseeable future.
37. On the contrary, it is likely to become ever more important due to the increasing globalization of markets and environmental concerns.
1.2.1 Market GlobalizationI ssues
1. Market globalization is increasingly occurring and this means that, to stay in business, manufacturing industries are necessarily placing increasing emphasis on issues of quality and efficiency.
2. Indeed, in today’s society, few if any companies can afford to be second best.
3. In turn, this focuses attention on the development of improved control systems so that processes operate in the best possible way.
4. In particular, improved control is a key enabling technology underpinning: • enhanced product quality • waste minimization • environmental protection • greater throughput for a given installed capacity 8 The Excitement of Control Engineering Chapter 1 • greater yield • deferring costly plant upgrades, and • higher safety margins.
5. All of these issues are relevant to the control of an integrated plant such as that shown in Figure 1.2.
6. Figure 1.2. Process schematic of a Kellogg ammonia plant 1.2.2 Environmental Issues All companies and governments are becoming increasingly aware of the need to achieve the benefits outlined above whilst respecting finite natural resources and preserving our fragile environment.
7. Again, control engineering is a core enabling technology in reaching these goals.
8. To quote one well known example, the changes in legislation covering emissions from automobiles in California have led car manufacturers to significant changes in technology including enhanced control strategies for internal combustion engines.
9. Section 1.3.
10. Historical Periods of Control Theory 9 Thus, we see that control engineering is driven by major economic, political, and environmental forces.
11. The rewards for those who can get all the factors right can be enormous.
1.3 Historical Periods of Control Theory
1. We have seen above that control engineering has taken several major steps forward at crucial times in history (e.g. the industrial revolution, the Second World War, the push into space, economic globalization, shareholder value thinking etc.).
2. Each of these steps has been matched by a corresponding burst of development in the underlying theory of control.
3. Early on, when the compelling concept of feedback was applied, engineers sometimes encountered unexpected results.
4. These then became catalysts for rigorous analysis.
5. For example, if we go back to Watt’s fly ball governor, it was found that under certain circumstances these systems could produce self sustaining oscillations.
6. Towards the end of the 19th century several researchers (including Maxwell) showed how these oscillations could be described via the properties of ordinary differential equations.
7. The developments around the period of the SecondWorldWar were also matched by significant developments in Control Theory.
8. For example, the pioneering work of Bode, Nyquist, Nichols, Evans and others appeared at this time.
9. This resulted in simple graphical means for analyzing single-input single-output feedback control problems.
10. These methods are now generally known by the generic term Classical Control Theory.
11. The 1960’s saw the development of an alternative state space approach to control.
12. This followed the publication of work by Wiener, Kalman (and others) on optimal estimation and control.
13. This work allowed multivariable problems to be treated in a unified fashion.
14. This had been difficult, if not impossible, in the classical framework.
15. This set of developments is loosely termed Modern Control Theory.
16. By the 1980’s these various approaches to control had reached a sophisticated level and emphasis then shifted to other related issues including the effect of model error on the performance of feedback controllers.
17. This can be classified as the period of Robust Control Theory.
18. In parallel there has been substantial work on nonlinear control problems.
19. This has been motivated by the fact that many real world control problems involve nonlinear effects.
20. There have been numerous other developments including adaptive control, autotuning, intelligent control etc.
21. These are too numerous to detail here.
22. Anyway, our purpose is not to give a comprehensive history but simply to give a flavor for the evolution of the field.
23. At the time of writing this book, control has become a mature discipline.
24. It is thus possible to give a treatment of control which takes account of many different viewpoints and to unify these in a common framework.
25. This is the approach we will adopt here.
26. 10 The Excitement of Control Engineering Chapter 1 1.
27. 4 Types of Control System Design Control system design in practice requires cyclic effort in which one iterates between modeling, design, simulation, testing, and implementation.
28. Control system design also takes several different forms and each requires a slightly different approach.
29. One factor that impacts on the form that the effort takes is whether the system is part of a predominantly commercial mission or not.
30. Examples where this is not the case include research, education and missions such as landing the first man on the moon.
31. Although cost is always a consideration, these types of control design are mainly dictated by technical, pedagogical, reliability and safety concerns.
32. On the other hand, if the control design is motivated commercially, one again gets different situations depending on whether the controller is a small sub-component of a larger commercial product (such as the cruise controller or ABSi n a car) or whether it is part of a manufacturing process (such as the motion controller in the robots assembling a car).
33. In the first case one must also consider the cost of including the controller in every product, which usually means that there is a major premium on cost and hence one is forced to use rather simple microcontrollers.
34. In the second case, one can usually afford significantly more complex controllers, provided they improve the manufacturing process in a way that significantly enhances the value of the manufactured product.
35. In all of these situations, the control engineer is further affected by where the control system is in its lifecycle, e.g.: • Initial grass roots design • Commissioning and Tuning • Refinement and Upgrades • Forensic studies 1.4.1 Initial Grass Roots Design In this phase, the control engineer is faced by a green-field, or so called grass roots projects and thus the designer can steer the development of a system from the beginning.
36. This includes ensuring that the design of the overall system takes account of the subsequent control issues.
37. All too often, systems and plants are designed based on steady state considerations alone.
38. It is then small wonder that operational difficulties can appear down the track.
39. It is our belief that control engineers should be an integral part of all design teams.
40. The control engineer needs to interact with the design specifications and to ensure that dynamic as well as steady-state issues are considered.
41. Section 1.5.System Integration 11 1.4.2 Commissioning and Tuning Once the basic architecture of a control system is in place, then the control engineer’s job becomes one of tuning the control system to meet the required performance specifications as closely as possible.
42. This phase requires a deep understanding of feedback principles to ensure that the tuning of the control system is carried out in an expedient, safe and satisfactory fashion.
43. 1.4.3 Refinement and Upgrades Once a system is up and running, then the control engineer’s job turns into one of maintenance and refinement.
44. The motivation for refinement can come from many directions.
45. They include • internal forces - e.g. the availability of new sensors or actuators may open the door for improved performance • external forces - e.g. market pressures, or new environmental legislation may necessitate improved control performance 1.4.4 “Forensic” Studies Forensic investigations are often the role of control engineering consultants.
46. Here the aim is to suggest remedial actions that will rectify an observed control problem.
47. In these studies, it is important that the control engineer take a holistic view since successful control performance usually depends on satisfactory operation of many interconnected components.
48. In our experience, poor control performance is as likely to be associated with basic plant design flaws, poor actuators, inadequate sensors, or computer problems as it is to be the result of poor control law tuning.
49. However, all of these issues can, and should be, part of the control engineer’s domain.
50. Indeed, it is often only the control engineer who has the necessary overview to successfully resolve these complex issues.
51. 1.5 System Integration As is evident from the above discussion, success in control engineering depends on taking a holistic viewpoint.
52. Some of the issues that are embodied in a typical control design include: • plant, i.e. the process to be controlled • objectives • sensors • actuators • communications 12 The Excitement of Control Engineering Chapter 1 • computing • architectures and interfacing • algorithms • accounting for disturbances and uncertainty These issues are briefly discussed below.
53. 1.5.1 Plant As mentioned in subsection 1.4.1, the physical layout of a plant is an intrinsic part of control problems.
54. Thus a control engineer needs to be familiar with the physics of the process under study.
55. This includes a rudimentary knowledge of the basic energy balance, mass balance and material flows in the system.
56. The physical dimensions of equipment and how they relate to performance specifications must also be understood.
57. In particular, we recommend the production of back of the envelope physical models as a first step in designing and maintaining control systems.
58. These models will typically be refined as one progresses.
59. 1.5.2 Objectives Before designing sensors, actuators or control architectures, it is important to know the goal, that is, to formulate the control objectives.
60. This includes • what does one want to achieve (energy reduction, yield increase, . . . ) • what variables need to be controlled to achieve these objectives • what level of performance is necessary (accuracy, speed, . . . ) 1.5.3 Sensors Sensors are the eyes of control enabling one to see what is going on.
61. Indeed, one statement that is sometimes made about control is: If you can measure it,you can control it.
62. This is obviously oversimplified and not meant literally.
63. Nonetheless, it is a catchy phrase highlighting that being able to make appropriate measurements is an intrinsic part of the overall control problem.
64. Moreover, new sensor technologies often open the door to improved control performance.
65. Alternatively, in those cases where particularly important measurements are not readily available then one can often infer these vital pieces of information from other observations.
66. This leads to the idea of a soft or virtual sensor.
67. We will see that this is one of the most powerful techniques in the control engineer’s bag of tools.
68. Section 1.5. System Integration 13 1.5.4 Actuators Once sensors are in place to report on the state of a process, then the next issue is the ability to affect, or actuate, the system in order to move the process from the current state to a desired state.
69. Thus, we see that actuation is another intrinsic element in control problems.
70. The availability of new or improved actuators also often opens the door to significant improvements in performance.
71. Conversely, inadequate, or poor, actuators often lie at the heart of control difficulties.
72. A typical industrial control problem will usually involve many different actuators - see, for example, the flatness control set-up shown in Figure 1.3. Figure 1.3. Typical flatness control set-up for rolling mill 1.5.5 Communications Interconnecting sensors to actuators, involves the use of communication systems.
73. A typical plant can have many thousands of separate signals to be sent over long distances.
74. Thus the design of communication systems and their associated protocols is an increasingly important aspect of modern control engineering.
75. There are special issues and requirements for communication systems with real time data.
76. For example, in voice communication, small delays and imperfections in transmission are often unimportant since they are transparent to the recipient.
77. However, in high speed real time control systems, these issues could be of major importance.
78. For example, there is an increasing tendency to use Ethernet type connections for data transmission in control.
79. However, as is well known by those familiar with this technology, if a delay occurs on the transmission line, then the transmitter simply tries again at some later random time.
80. This obviously introduces a non-deterministic delay into the transmission of the data.
81. Since all control 14 The Excitement of Control Engineering Chapter 1 systems depend upon precise knowledge of, not only what has happened, but when it happened, attention to such delays is very important for the performance of the overall system.
82. 1.5.6 Computing In modern control systems, the connection between sensors and actuators is invariably made via a computer of some sort.
83. Thus, computer issues are necessarily part of the overall design.
84. Current control systems use a variety of computational devices including DCS’s (Distributed Control Systems), PLC’s (Programmable Logic Controllers), PC’s (Personal Computers), etc.
85. In some cases, these computer elements may be rather limited with respect to the facilities they offer.
86. As with communication delays, computational delays can be crucial to success or failure in the operation of control systems.
87. Since, determinism in timing is important, a multi-tasking real-time operating system may be required.
88. Another aspect of computing is that of numerical precision.
89. We know of several control systems that failed to meet the desired performance specifications simply because of inadequate attention to numerical issues.
90. For this reason, we will devote some attention to this issue in the sequel.
91. A final computer based question in control concerns the ease of design and implementation.
92. Modern computer aided tools for rapid prototyping of control systems provide integrated environments for control system modeling, design, simulation and implementation.
93. These pictures to real time code facilities have allowed development times for advanced control algorithms to be reduced from many months to the order of days or, in some cases, hours.
94. 1.5.7 Architectures and Interfacing The issue of what to connect to what is a non-trivial one in control system design.
95. One may feel that the best solution would always be to bring all signals to a central point so that each control action would be based on complete information (leading to so called, centralized control).
96. However, this is rarely (if ever) the best solution in practice.
97. Indeed, there are very good reasons why one may not wish to bring all signals to a common point.
98. Obvious objections to this include complexity, cost, time constraints in computation, maintainability, reliability, etc.
99. Thus one usually partitions the control problem into manageable sub-systems.
100. How one does this is part of the control engineer’s domain.
101. Indeed, we will see in the case studies presented in the text that these architectural issues can be crucial to the final success, or otherwise, of a control system.
102. Indeed, one of the principal tools that a control system designer can use to improve performance is to exercise lateral thinking relative to the architecture of the control problem.
103. As an illustration, we will present a real example later in the text (see Chapter 8) where thickness control performance in a reversing rolling mill is irrevocably constrained by a particular architecture.
104. It is shown that no improvement in actuators, sensors or algorithms (within this architecture) can remedy the probSection 1.5. System Integration 15 lem.
105. However, by simply changing the architecture so as to include extra actuators (namely the currents into coiler and uncoiler motors) then the difficulty is resolved (see Chapter 10).
106. As a simpler illustration, the reader is invited to compare the difference between trying to balance a broom on one’s finger with one’s eyes open or shut.
107. Again there is an architectural difference here - this time it is a function of available sensors.
108. A full analysis of the reasons behind the observed differences in the difficulty of these types of control problems will be explained in Chapters 8 and 9 of the book.
109. We thus see that architectural issues are of paramount importance in control design problems.
110. A further architectural issue revolves around the need to divide and conquer complex problems.
111. This leads to a hierarchical view of control as illustrated in Table 1.1 Level Description Goal Time frame Typical design tool 4 Plant wide optimization Meeting customer orders and scheduling supply of materials Everyday (say) Static optimization 3 Steady state optimization at unit operational level Efficient operation of a single unit (e.g. distillation column) Every hour (say) Static optimization 2 Dynamic control at unit operation level Achieving set-points specified at level 3 and achieving rapid recovery from disturbances Every minute (say) Multivariable control, e.g. Model Predictive Control 1 Dynamic control at single actuator level Achieving liquid flow rates etc as specified at level 2 by manipulation of available actuators (e.g. valves) Every second (say) Single variable control, e.g. PID Table 1.1. Typical control hierarchy Having decided what connections need to be made, there is the issue of interfacing the various sub-components.
112. This is frequently a non-trivial job as it is often true that special interfaces are needed between different equipment.
113. Fortunately vendors of control equipment are aware of this difficulty and increasing attention is being paid to standardization of interfaces.
114. 16 The Excitement of Control Engineering Chapter 1 1.5.8 Algorithms Finally, we come to the real heart of control engineering i.e. the algorithms that connect the sensors to the actuators.
115. It is all to easy to underestimate this final aspect of the problem.
116. As a simple example from the reader’s everyday experience, consider the problem of playing tennis at top international level.
117. One can readily accept that one needs good eye sight (sensors) and strong muscles (actuators) to play tennis at this level, but these attributes are not sufficient.
118. Indeed eye-hand coordination (i.e. control) is also crucial to success.
119. Thus beyond sensors and actuators, the control engineer has to be concerned with the science of dynamics and feedback control.
120. These topics will actually be the central theme of the remainder of this book.
121. As one of our colleagues put it; Sensors provide the eyes and actuators the muscle but control science provides the finesse.
122. 1.5.9 Disturbances and Uncertainty One of the things that makes control science interesting is that all real life systems are acted on by noise and external disturbances.
123. These factors can have a significant impact on the performance of the system.
124. As a simple example, aircraft are subject to disturbances in the form of wind gusts, and cruise controllers in cars have to cope with different road gradients and different car loadings.
125. However, we will find that, by appropriate design of the control system, quite remarkable insensitivity to external disturbances can be achieved.
126. Another related issue is that of model uncertainty.
127. All real world systems have very complex models but an important property of feedback control is that one can often achieve the desired level of performance by using relatively simple models.
128. Of course, it is beholden on designers to appreciate the effect of model uncertainty on control performance and to decide if attention to better modeling would enable better performance to be achieved.
129. Both of the issues raised above are addressed, in part, by the remarkable properties of feedback.
130. This concept will underpin much of our development in the book.
131. 1.5.10 Homogeneity A final point is that all interconnected systems, including control systems, are only as good as their weakest element.
132. The implications of this in control system design are that one should aim to have all components (plant, sensors, actuators, communications, computing, interfaces, algorithms, etc) of roughly comparable accuracy and performance.
133. If this is not possible, then one should focus on the weakest component to get the best return for a given level of investment.
134. For example, there is no point placing all one’s attention on improving linear models (as has become fashionable in parts of modern control theory) if the performance limiting factor Section 1.5. System Integration 17 is that one needs to replace a sticking valve or to develop a virtual sensor for a key missing measurement.
135. Thus a holistic viewpoint is required with an accurate assessment of error budgets associated with each sub-component.
136. 1.5.11 Cost Benefit Analysis Whilst on the subject of ensuring best return for a given amount of effort it is important to raise the issue of benefits analysis.
137. Control engineering, in common with all other forms of engineering, depends on being able to convince management that there is an attractive cost-benefit trade-off in a given project.
138. Payback periods in modern industries are often as short as 6 months and thus this aspect requires careful and detailed attention.
139. Typical steps include: • assessment of a range of control opportunities • developing a short list for closer examination • deciding on a project with high economic or environmental impact • consulting appropriate personnel (management, operators, production staff, maintenance staff etc) • identifying the key action points • collecting base case data for later comparison • deciding on revised performance specifications • updating actuators, sensors etc • development of algorithms • testing the algorithms via simulation • testing the algorithms on the plant using a rapid prototyping system • collecting preliminary performance data for comparison with the base case • final implementation • collection of final performance data • final reporting on project 18 The Excitement of Control Engineering Chapter
140. 1 1.6 Summary
141. • Control Engineering is present in virtually all modern engineering systems
142. • Control is often the hidden technology as its very success often removes it from view
143. • Control is a key enabling technology with respect to ◦ enhanced product quality ◦ waste and emission minimization ◦ environmental protection ◦ greater throughput for a given installed capacity ◦ greater yield ◦ deferring costly plant upgrades, and ◦ higher safety margins
144. • Examples of controlled systems include System Controlled outputs include Controller Desired performance includes Aircraft Course, pitch, roll, yaw Autopilot Maintain flight path on a safe and smooth trajectory Furnace Temperature Temperature controller Follow warm-up temperature profile, then maintain temperature Wastewater treatment pH value of effluent pH controller Neutralize effluent to specified accuracy Automobile Speed Cruise controller Attain, then maintain selected speed without undue fuel consumption
145. • Control is a multidisciplinary subject that includes ◦ sensors ◦ actuators ◦ communications ◦ computing ◦ architectures and interfacing ◦ algorithms
146. • Control design aims to achieve a desired level of performance in the face of disturbances and uncertainty Section 1.7.Further Reading 19
147. • Examples of disturbances and uncertainty include System Actuators Sensors Disturbances Uncertainties Aircraft Throttle servo, rudder and flap actuators, etc.
148. Navigation instruments Wind, air pockets, etc.
149. Weight, exact aerodynamics, etc.
150. Furnace Burner valve actuator Thermocouples, heat sensors Temperature of incoming objects, etc.
151. Exact thermodynamics, temperature distribution Wastewater treatment Control acid valve servo pH sensor Inflow concentration pH gain curve, measurement errors Automobile Throttle positioning Tachometer Hills Weight, exact dynamics 1.
152. 7 Further Reading Historical notes The IEEE History Centre and its resources are an excellent source for the historically interested reader.
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