Knowledge of fundamentals physical or empirical modeling
Knowledge of fundamentals on dynamical behavior and stability
Understanding and design techniques of a PID controller
Knowledge of the fundamentals of MATLAB as a numerical tool for the theoretical topics studied
Lectures and class exercises.
Should teaching be carried out in mixed mode or remotely, it may be necessary to introduce changes with respect to previous statements, in line with the programme planned and outlined in the syllabus.
1. INTRODUCTION TO PROCESS CONTROL
Introductory considerations on control. Control objectives and benefits.
2. MODELLING OF CHEMICAL PROCESSES
Mathematical modelling principles. Balancing equations, procedures and examples. Linearization.
3. PROCESS DYNAMICS
The Laplace Transform. Input-output models. Transfer functions. Block diagrams. Response to canonical inputs. Response to arbitrary signals. Frequency response
4. DYNAMIC BEHAVIOR OF TYPICAL PROCESS SYSTEMS
Dynamic behavior of first order systems. Dynamic behaviour of second order systems. Dynamic behaviour of first order systems with dead time. Pole dominance
The concept of stability. Stability and location of poles. Criteria for analysis of stability. Routh test. Bode criterion.
6. EMPIRICAL MODEL IDENTIFICATION
Introduction. Empirical Model building procedure. The process reaction curve. Statistical model identification.
7. PID CONTROLLERS
The feedback loop. The PID algorithm. Proportional, integral and derivative mode. The PID controller. Methods for PID tuning: PID controller tuning for dynamic performance. Methods for PID tuning: the Ziegler-Nichols closed-loop method. Digital implementation of PIDs. Practical issues of PID application.
8. ENHANCEMENTS TO SINGLE-LOOP PID FEEDBACK CONTROL
General principles. Cascade control. Feedforward control.
Matlab excercises for the topics covered by theory.
1. T. E. Marlin, Process Control, McGraw Hill, 2nd Ed.
2 J. J. D’Azzo, C. H. Houpis, Linear control system analysis and design, McGraw Hill, 4th Ed.