2. Professors
  3. CACCAVO DIEGO
  4. Teaching

MODELING AND CONTROL FOR PROCESS INDUSTRIES

DIEGO CACCAVO MODELING AND CONTROL FOR PROCESS INDUSTRIES

0622200024
DEPARTMENT OF INDUSTRIAL ENGINEERING
EQF7
CHEMICAL ENGINEERING
2024/2025



OBBLIGATORIO
YEAR OF COURSE 1
YEAR OF DIDACTIC SYSTEM 2024
SPRING SEMESTER
CFUHOURSACTIVITY
440LESSONS
220EXERCISES
DIEGO CACCAVO T Curriculum
Objectives
Knowledge and understanding
Classification of mathematical models: with concentrated and distributed parameters, stationary and dynamic; linear e not; based on ODE or PDE equations; in continuous or discrete time. First principles models. Models based on transport phenomena. SISO and MIMO systems; Inlet-outlet oriented models and models with representation in the state space. Logistic map. Time series. empirical and statistical models. Models based on population balance. Numerical solution of parabolic PDEs. Fundamentals of the problems of constrained and unconstrained, linear and non-linear optimization. Definition of stability for systems with input-output representation, in state space, both linear and non-linear.

Applied knowledge and understanding - engineering analysis:
Knowing how to classify mathematical models. Understanding of the meaning and implications of the representation adopted in dynamic systems for the time, continuous or discrete, entails. Ability to distinguish the level of complexity appropriate for the system description of the industrial plants of process for the definition and resolution of the appropriate mathematical model.

Applied knowledge and understanding - engineering design
Choice and design (identification of parameters) of a control system. Dynamics modeling
of a transient system.

Independent judgment - engineering practice:
Discriminating between stable, marginally stable and always unstable linear dynamical systems. Distinguish the differences in behavior, conceptual and practical, in steady or dynamic conditions, between linear systems and non-linear. Set the gain of a PID controller as a single controller in relation to stability. Knowing recognize the most common linear dynamical systems source of closed-loop BIBO instability and take the related countermeasures. Verify and discuss the BIBO stability of a controlled linear dynamic system in feedback with the use of software.

Transversal skills - communication skills:
Knowing how to prepare and manage an interactive session on a PC with the use of software, equipped with an interface both alphanumeric and graphic. Knowing how to carry out a practical test on a PC in which to report the discussion of a problem.

Transversal skills - ability to learn:
Knowing how to apply the knowledge acquired to contexts different from those presented during the course, and deepen the topics covered using materials other than those proposed.
Prerequisites
It's crucial to have a strong understanding of the fundamental concepts of chemical engineering, with particular emphasis on material and energy balances under non-steady-state conditions, the concept of transfer functions, and basic knowledge of feedback control. Additionally, a basic understanding of mathematical analysis, especially regarding ordinary differential equations, is necessary.
Contents
1.Introduction and Purpose of the Course (2 hours of theory)
2.Feedback Control Systems (25 hours, composed as follows: 13 hours of theory, 12 hours of exercises)
Block algebra. Introduction to MATLAB® (Control System Toolbox) and Simulink. Root locus for the study of BIBO stability. Root locus as a tool for designing controllers/compensators: P, PI, PD, PID, lead, lag, and lead-lag. Frequency response: Bode and Nyquist diagrams and their stability criteria.
3.Other Problems, Strategies, or Advanced Control Architectures (10 hours, composed as follows: 6 hours of theory, 4 hours of exercises)
Inverse response systems. Smith predictor. Feedforward, cascade, ratio, adaptive, inferential, and multivariable controls. An overview of model predictive control (MPC).
4.Mathematical Modeling (13 hours, composed as follows: 8 hours of theory, 5 hours of exercises) Classification of mathematical models. System identification. Representation of dynamic systems in state space.
5.Introduction to the nonlinear systems dynamics (10 hours, composed as follows: 6 hours of theory, 4 hours of exercises) One-dimensional systems, fixed points and linearization, stability and bifurcations. Two-dimensional systems, phase portrait, fixed points and linearization, limit cycles. Iterative maps.
Teaching Methods
The course consists of lectures (35 hours) and classroom exercises (25 hours) for a total of 60 hours worth 6 credits.

The exercises are conducted collaboratively under the guidance of the instructor. Some of them involve the use of MATLAB® software to solve ODEs and to analyze and design control systems, using the Control System Toolbox and Simulink tools. Each student can download and use the software on their own computer using the "MATLAB Campus-Wide License" provided by the University of Salerno.

Attendance at lectures is strongly recommended.
Verification of learning
The assessment of the achievement of the objectives is verified through a written exam and a subsequent oral interview.
In the final exam, the following criteria will be considered:
A) Understanding and ability to solve the main problems requiring the application of expressed concepts;
B) Mastery of basic assumptions and the underlying logic of the discipline;
C) Ability to extend the use of basic concepts to address new situations;
D) Language proficiency with particular reference to the specific terminology of the discipline.

The written test, lasting two hours, is structured as an "open book" exam, allowing candidates to use any educational material, such as books, notes, and the like (excluding internet access), and employs MS Word® and MATLAB® software along with their respective applications. The theme of the test will focus on the topics covered during the course, with particular attention to linear or linearizable control systems. Specifically, it will focus on the design process of control architecture and the controller, as well as the evaluation of the BIBO stability of such systems, in addition to system identification and nonlinear dynamics.

The level of sufficiency corresponds to demonstrating the ability to identify the methodological tools to be used, correctly formulate the problems, and indicate feasible paths for resolution. The level of excellence is achieved by providing correct answers to all questions posed by the test.
Texts
Reference textbooks
1.George Stephanopoulos, Chemical Process Control: An Introduction to Theory and Practice, Ptr Prentice Hall (1983), ISBN-13: 978-0131286290
2.Dale E. Seborg, Thomas F. Edgar, Duncan A. Mellichamp, Francis J. Doyle III, Process Dynamics and Control, Wiley (2019), ISBN-13: 978-1119587491

Feedback control systems:
3.Norman S. Nise, Control Systems Engineering 8th ed., Wiley (2022), ISBN-13: 978-1119590132
4.Paolo Bolzern, Riccardo Scattolini, Nicola Schiavoni, Fondamenti di controlli automatici IV ed., McGraw-Hill Education (2015), ISBN-13: 978-8838668821
5.Gene F. Franklin, J. David Powell, Abbas Emami-Naeini, Feedback Control of Dynamic Systems, Pearson (2019), ISBN-13: 978-1292274522
Nonlinear dynamics:
6.Steven H. Strogatz, Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering, CRC Press (2024), ISBN-13: 978-0367026509McGraw-Hill Education (2011), ISBN-13: 978-8838672750
More Information
The course is taught in Italian.
Lessons Timetable

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