1. CSE 425: Industrial Process Control 1

2. About the course Lect.TuLabTotal 32-5 45Semester work 80Final 125Total Grading Scheme Course webpage: http://www.staff.zu.edu.eg/amabd/http://www.staff.zu.edu.eg/amabd/ http://www.amelanany.faculty.zu.edu.eg/ Reference textbook Pao C. Chau, Process control a first course with Matlab, Cambridge University Press, 2002. 2

3. Topics to be covered: 1 Introduction 2 Mathematical Preliminaries 3 Dynamic Response 5 Analysis of Single-Loop Control Systems 6 Design and Tuning of Single-Loop Control Systems 8 Frequency-Response Analysis 9 Design of State-Space Systems 10 Multiloop Systems 3

4. Introduction In the processing industry, controllers play a crucial role in keeping our plants running virtually everything from simply filling up a storage tank to complex separation processes and chemical reactors. 4

5. Introduction Let’s take a look at a bioreactor. To find out if the bioreactor is operating properly, we monitor variables such as: - temperature, - pH, - dissolved oxygen, - liquid level, - feed flow rate, - the concentration of chemicals. 5

6. FEEDBACK CONTROL makes use of an output of a system to influence an input to the same system. CONTROL (verb): To maintain desired conditions in a physical system by adjusting selected variables in the system. input = cause output = effect Introduction 6

7. Let’s use the pH as an example. 7

8. Introduction To consider pH as a controlled variable, we use a pH electrode to measure its value and, with a transmitter, send the signal to a controller, which can be a little black box or a computer. The controller takes in the pH value and compares it with the desired pH, what is called the set point or the reference. If the values are not the same, there is an error, and the controller makes proper adjustments by manipulating the acid or the base pump – the actuator. The adjustment is based on calculations made with a control algorithm, also called the control law. The error is calculated at the summing point, where we take the desired pH minus the measured pH. Because of how we calculate the error, this is a negative-feedback mechanism. 8

9. WHAT DOES A FEEDBACK SYSTEM DO? Caution: Common misunderstanding in terminology! Common vernacular Negative feedback: “You are an idiot! Positive feedback: That was a good idea. Thank you! Engineering & Science Positive feedback: Action to increase the error from desired. Negative feedback: Action to reduce the error from desired. Good! 9

10. Introduction This simple pH control example is what we call a single-input single-output (SISO) system; the single input is the set point and the output is the pH value. This simple feedback mechanism is also what we call a closed loop. 10

11. Stability and Robustness Implementation of a controller may lead to instability, and the issue of system stability is a major concern. The control system also has to be robust such that it is not overly sensitive to changes in process parameters. 11

12. Servo vs. Regulatory Control When we change a specific operating condition, meaning the set point, we would like, for example, the pH of the bioreactor to follow our command. This is what we call servocontrol. The pH value of the bioreactor is subjected to external disturbances (also called load changes), and the task of suppressing or rejecting the effects of disturbances is called regulatory control. 12

13. Some issues in designing a control system: First: identify the role of various variables. – what we need to control, – what we need to manipulate, – what the sources of disturbances are. We then need to state our design objective and specifications: – servo or regulation, – the desired response of the system. 13

14. To achieve these goals: – Select the proper control strategy and controller. – To implement the strategy, we also need to select the proper sensors, transmitters, and actuators. – After all is done, we have to know how to tune the controller. 14

15. The Need for Process Models The design procedures depend heavily on the dynamic model of the process to be controlled. The dynamic model can be obtained – From first principles, or – Empirically, using system identification Control problems are transient in nature. Accordingly, we include the time-derivative (also called accumulation) term in our balance (model) equations. 15

16. Mathematical tools that we use In classical control, our analysis is based on linear ordinary differential equations with constant coefficients – what is called linear time invariant (LTI). To handle our linear differential equations, we rely heavily on Laplace transform, and we invariably rearrange the resulting algebraic equation into the so-called transfer functions. However, we rarely go as far as solving for the time-domain solutions. Much of our analysis is based on our understanding of the roots of the characteristic polynomial of the differential equation – what we call the poles. 16

17. Why process control? One word: DISTURBANCES! We want to achieve the following: 1. Safety 2. Environmental Protect. 3. Equipment protect. 4. Smooth operation 5. Product quality 6. Profit 7. Monitoring and diagnosis 17

18. T A CBCB v1 v2 Final element Sensors Computing and interface for person Communication Control Equipment 18

19. Sensors, local indicators, and valves in the process Displays of variables, calculations, and commands to valves are in the centralized control center. Central control room Where is Control done? 19

20. LC FC TC A Piping and instrumentation (P&I) drawings provide documentation. We use standard symbols. F = flow L = level P = pressure T = temperature ….. How is Control Design Documented? 20

21. WORKSHOP 1 You are implementing control “manually”. a. Explain the principle for a typical flow sensor b. Explain how the final element affects the controlled variable. c. Explain the correct action if you want to increase the controlled variable pump valve sensor Flow Control 21

22. WORKSHOP 2 You are implementing control “manually”. a. Explain the principle for a typical liquid level sensor b. Explain how the final element affects the controlled variable. c. Explain the correct action if you want to increase the controlled variable Level Control pumpvalve sensor 22

23. BENEFITS FROM PROCESS CONTROL When we control a process, we reduce the variability of key variables. Without feedback control Composition (% H. Key) Reflux valve 23

24. BENEFITS FROM PROCESS CONTROL When we control a process, we reduce the variability of key variables. With feedback control Composition (% H. Key), note smaller scale Reflux valve Variability is moved from controlled to manipulated variable! 24