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Faculty of Engineering and Applied Science

CHEE 434 – PROCESS CONTROL II

Course Syllabus – Winter 2020

This is your course syllabus. Please download the file and keep it for future reference.

TEACHING TEAM

COURSE INSTRUCTOR

Martin Guay, PhD

Chemical Engineering

Queen’s University

E-mail: martin.guay@queensu.ca

Please check the course website for an up-to-date list of TAs and other course personnel.

CHEE 434 – Process Control II Winter 2020

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COURSE INFORMATION

COURSE DESCRIPTION

This course presents methods for dynamic analysis and controller design for multivariable

process control problems, and discrete time control. Control techniques, including anti-reset

windup, internal model principle, feedforward and cascade control, are discussed and

analyzed. An introduction to the theory of Model predictive control is presented. Multivariable

controller design and the problem of control loop interaction are examined. State space models

for processes are introduced. Mathematical tools for analyzing the dynamics of sampled data

systems are developed, and the design of discrete time controllers is introduced. Techniques

discussed in the course are applied to the control of various chemical process units. (0/0/0/30/12)

PREREQUISITES: CHEE 319 or permission of the department.

COURSE LEARNING OUTCOMES (CLO)

The basic objective of this course is to provide a comprehensive introduction to the concept of

controller design for dynamical control systems. We will consider primarily a model-based

approach where the dynamics of the process to be controlled have been modeled adequately

using either black box or mechanistic models and for which a satisfactory description of the model

uncertainties have been characterised. Both state-space and input-output modeling formulations

will be considered. Since most models cannot represent the behaviour of a given process exactly,

the effect of modeling errors on controller design will form a consistent theme throughout this

course. Throughout the course, the students will consider some of the most prominent controller

design techniques currently available. We will first emphasize the development of control system

analysis tools for continuous-time and discrete-time linear systems. We also revisit frequency

response analysis techniques such as Bode diagrams, the Nyquist stability criterion and introduce

a robust stability criterion for a class of uncertain linear systems.

The primary emphasis will be on controller design techniques, in particular, model-based

controller design. We will first consider the design for single-input/single-output (SISO)

continuous time and discrete time linear systems. The course will attempt to assemble a set of

tools for the design of controller in the presence of delay, model uncertainties and process

disturbances.

One of major challenges in this course (and control engineering practice) is the design of

controllers for Multi-input/Multi-output systems (MIMO). We will first consider generalizations

of the techniques developed for SISO systems. More general techniques based on the state-space

will also be considered.

At the final stage of the course, we will study optimization-based control techniques and, in

particular, model predictive control (MPC). MPC has been widely recognized in the chemical and

petrochemical industry and forms the basis of most industrial multivariable controllers.

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Specific course learning outcomes include:

CLO DESCRIPTION INDICATORS

CLO 1 Recognize the importance of modeling errors and uncertainties in

controller design.

KB-Proc(d)

DE-Define

CLO 2 Apply modern control theory to design a controller for uncertain

SISO and MIMO linear dynamical systems

KB-Proc(d)

DE-Solutions

CLO 3 Understand the trade-off in performance that arise in the design

of a controller.

KB-Proc(d)

DE-Assess

This course assesses the following program indicators:

Knowledge base for engineering (KB)

KB-Proc(d) Derives transfer function models from dynamic process models and process data to

apply control theory.

Design (DE)

DE-Define Define problem, objectives and constraints.

DE-Solutions Create a product, process or system to solve a problem, that meets specified needs,

and subject to appropriate iterations.

DE-Assess Evaluate performance of a design, using criteria that incorporates specifications,

limitations, assumptions, constraints, and other relevant factors.

COURSE STRUCTURE AND ACTIVITIES

3 lecture hours + 1 tutorial hour per week. Please refer to SOLUS for times and locations.

EXPECTATIONS FOR LECTURES/TUTORIALS

Lecture slides will be posted in advance. Some lectures will include examples and problem

solutions not contained in the posted slides. Students are expected to read associated sections

and study worked examples in the textbook. Students are expected to bring a copy of the

tutorial problem (posted in advance) to class.

COURSE MATERIALS

G.C. Goodwin, S.F. Graebe and M.E. Salgado, Control System Design¸ Prentice Hall, Upper

Saddle River, NJ (2001);

View the textbook website at http://csd.newcastle.edu.au/control/

Other Material

Matlab / Simulink are available in the computer cluster, Dupuis Hall, and in the teaching studio

(Room 213, Beamish-Munro Hall).

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All course lecture slides, assignments and tutorials will be posted on the course website, or

Learning Management System.

COURSE EVALUATION

Deliverable Week or Date Weight

2 Quizzes Week 6 and 10 30%

Project Week 10 10%

Final Exam Exam period 60%

All assessments in this course will receive numerical percentage marks. The final grade you

receive for the course will be derived by converting your numerical course average to a letter

grade according to the established Grade Point Index.

Unless other arrangements have been approved, departmental policies regarding late and missed

assignments, and missed quizzes/exams will be followed. Only a Casio 991 non-programmable,

non-communicating calculator will be allowed during tests and exams.

COURSE POLICIES Please review the following policies concerning copyright, academic integrity, absences and

academic accommodations:

COPYRIGHT

Unless otherwise stated, the material on the course website is copyrighted and is for the sole use

of students registered in this course. The material on the website may be downloaded for a

registered student’s personal use but shall not be distributed or disseminated to anyone other

than students registered in this course.

ACADEMIC INTEGRITY

Information on policies concerning academic integrity is available in the Queen’s University

Code of Conduct, in the Senate Academic Integrity Policy Statement, on the Faculty of

Engineering and Applied Science website, and from your instructor.

ABSENCES (ACADEMIC CONSIDERATION) AND ACADEMIC ACCOMMODATIONS

For absences and academic accommodations please review the information on the FEAS

website.

TECHNICAL SUPPORT

No specialized computer-related technical skills are required for this course. If you require

technical assistance, please contact Technical Support.

PERSONAL SUPPORTIVE COUNSELLING

If at any time you find yourself feeling overwhelmed, anxious, sad, lonely, or distressed,

consider confidential supportive counselling offered by the Faculty of Engineering and Applied

Science.

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CHEE 434 || Module overview

Course learning outcomes (CLO): Students will be able to:

1. Recognize the importance of modeling errors and uncertainties in controller design. 2. Apply modern control theory to design a controller for uncertain SISO and MIMO linear dynamical systems 3. Understand the trade-off in performance that arise in the design of a controller

Students are expected to augment lecture material through reading of associated sections of the textbook, and to practice execution of course principles by completing posted problem sets

Module Lecture approach and content Tutorial approach and content Assessment (CLO, and % of course grade)

Module 1 (Wks 1)

Introduction to Process Control

What/where/why/how of process control

Objectives for process control

Motivation for process control Piping and Instrumentation Diagrams

(P&IDs) – conventions and interpretation

Economic justification for process control

Worked examples, based on lecture material

A set of practice problems is also posted (unmarked)

Material is included on mid-term (CLO1)

Module 2 (Wks 2-6)

Modeling and Analyzing Process Dynamics

Heat and material balance equations, constitutive relationships

Deciding on assumptions, and assessing their impact while modeling

Degrees of freedom analysis Linearization and deviation variables –

for single equations and systems of equations

Linear and nonlinear state space representation - states, inputs, outputs

Worked examples, based on lecture material

A set of practice problems is also posted (unmarked)

Material is included on mid-term (CLO1)

Design assignment 1 (10%, CLO1, CLO4)

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Review of Laplace transforms, their use and important properties

Interpreting transfer functions – stability, gains, poles, zeros, damping coefficient

Standard forms for transfer functions – e.g., gain-time constant form

Types of dynamic responses and characterization

Introduction to multi-input multi-output models and control

Obtaining transfer functions from state space representations

Dynamic structure of processes and systems – series interacting/non-interacting, parallel

Frequency response analysis for open-loop processes

Computer-based tutorials

Quiz 1 Covers Modules 1 and 2 Quiz 1: 2-3 questions will target CLO1, CLO2 and CLO3, worth 20% of course grade

Module 3 (Wks 7-10)

Feedback Control and Controller Design

Control-loop elements – impact on dynamics, basis for selection – accuracy versus range, reproducibility

Failure modes for actuators Elements of a feedback loop Closed-loop transfer functions and

assessing stability and performance Disturbance rejection (load ) problem Setpoint tracking (servo) problem Design considerations – pairing

manipulated and controlled variables PID control

Worked examples, based on lecture material

A set of practice problems is also posted (unmarked)

Computer-based tutorials

Material is included on final (CLO1, CLO2)

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Frequency response analysis for assessing closed-loop stability – Bode and Nyquist approaches

Performance criteria for controlled and manipulated variables

Direct Synthesis and Internal Model Control-based designs and tuning

Quiz 2 Covers Module 3 Quiz 1: 2-3 questions will target CLO4, CLO5, CLO6 and CLO7, worth 20% of course grade

Module 4 (Wks 11-12)

Controller Enhancements and Extensions

Cascade control – when and how to use – controller components associated with cascade control

Feedforward control – when and how to use, and associated controller components

Multi-loop controllers

Worked examples, based on lecture material

A set of practice problems is also posted (unmarked)

Computer-based tutorials

Material is included on final (CLO1, CLO2)

EXAM Final exam: One-two questions will target each CLO, worth 60% of course grade