MODELING AND SIMULATION
Learning outcomes of the course unit
The aim of this course is to provide the theoretical bases and the practical tools for modelling continuous, discrete, linear and non linear systems we can find in industrial processes and services. We start from the physical analysis and from the experimental results describing the process and we derive the transfer function between the input and the output of the process. This analytical function is then implemented on PC by simulation tools like Matlab-Simulink and the final product is a simulator of the original process, which can be used for engineering purposes like design, testing, revamping, training and so on. Finally, the model and the simulator are the basis for optimal designing and testing the modern control and automation functions. The aim of the regular lectures is to increase the technical and economic know-how on the design and implementation of automation systems for industrial applications. The aim of the laboratory sessions is to create the practical skill on off-the-shelf simulation tools also adopted in many industrial environments.
The pre-required knowledges for this course are included in the physical/ mathematical background taught during the first three-year courses. May be also helpful to know the fundamentals of the course : ¿ Basi di Dati e Sistemi Informativi¿ ING-INF/05.
Course contents summary
Industrial processes and general management
- Energetic and economic balance of industrial processes in a real time environment
- Energetic and environmental constraints of industrial processes
- The economic target value of the automation system versus the plant global budget
- The economic impact of the automation performance on the plant annual revenue
- The primary role of the automation system in optimal operating the process
- The knowledge of the process model as a key for optimizing the process performance
From the physical sytem to the mathematical model
- Continuous systems models of continuous industrial processes
- Discrete systems models of deterministic and stochastic discrete processes
- Time response and frequency response of linear systems; the exercises are carried out using the Matlab environment.
- Non linear devices in industrial processes ; the steady state condition and the dynamic behaviour in a large and in a little boundary of the steady state condition.
- Dynamical models of the most important electronic devices for industrial applications
Linear analisys of dynamical systems about the equilibrium point
- Frequency analysis and Laplace transform; the exercises are carried out using the Simulink environment.
- Open loop and closed loop systems: the impact of the negative feedback on the closed loop dynamical behaviour
- Simple and asymptotic stability : Nyquist and Bode criteria ; the rootlocus method . Some exercises are carried out using the TFI tool included in Matlab
- Transport delays in the loop and their effects on the stability margins.
Industrial simulators and their applications in process management
- Discrete system simulators for designing production chains
- Replica simulators for crew training and for in-factory testing of the control devices
- Real time and accelerated time simulators for diagnostic purposes.
- Real time and accelerated time simulators for optimizing processes and for mitigating the consequences of unespected contingencies
Process control and automation
- Continuous and discrete control systems : PID controllers, finite states automata, PLC based controllers.
- Designing the plant automation taking into account the dynamical model of the process.
- Human factors in process control : behavioural models, th
Cavallaro A., Setola R., Vasca F. :Guida operativa a Matlab, Simulink e Control Toolbox, Liguori ed , 2000
Marro G. : Controlli Automatici V ed. , Zanichelli, 2004
Carlucci D. : Teoria dei Sistemi ad Eventi Discreti, UTET 1998
Bridger R. S. : Introduction to Ergonomics , Taylor & Francis , II ed. , 2003
Veronesi M. : Regolazione PID, Franco Angeli, 2006
Balduzzi F., Calafiore G. : Esercizi di Automazione , UTET, 2000
Shinners S. M. : Advanced Modern Control System Theory and Design ,John Wiley & Sons, Inc , 1998
The regular lectures are supported by slides and by the video-projector driven by the teacher¿s PC. On this computer we develop and run in real time a set of suitable models for assessing the theory achievements in the field of the process modelling and of the automatic control. Some of these models are developed in cooperation with the student people.
The primary focus of the teaching method is put on the physical laws which describe the mass and energy balance of the industrial processes. The resulting differential and algebraic equations are then developed by mathematical tools like matrix algebra, Laplace transform, Fourier analysis and so on, building the final model of the process. Then we translate this model into a continuous or discrete simulator of the process, like Matlab-Simulink, and we can first test the model versus the experimental results and then we can use the simulator for design purposes.The laboratory exercises are carried out bimonthly on individual PCs by the student teams (2-3 students per team) making use of Matlab-Simulink, TFI, Statetra. The aim is to practically experiment the dynamical behaviour of the continuous and discrete processes just presented during the regular lectures. Besides, some practical exercises concern the Field Bus test set, in order to acquire experience on this new technology and on its impact in the automation design and in the maintenance management.
A final written test is foreseen, followed by an oral test. Two midterm written tests are foreseeen: if the average score is > =18/30, the final written test may be avoided; if the average score is >=24/30 also the oral test is optional.