MODELING AND SIMULATION
cod. 08390

Academic year 2009/10
2° year of course - First semester
Professor
Academic discipline
Automatica (ING-INF/04)
Field
Ambito aggregato per crediti di sede
Type of training activity
Hub-specific activity
81 hours
of face-to-face activities
9 credits
hub:
course unit
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Learning objectives

<br />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. <br /> 

Prerequisites

<br />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 unit content

<br /> <br />Industrial processes and general management <br />-         Energetic and economic balance of industrial processes in a real time environment <br />-         Energetic and environmental constraints of industrial processes<br />-         The economic target value of the automation system versus the plant global budget <br />-         The economic impact of the automation   performance on the plant annual revenue <br />-    The primary role of the automation system in optimal operating the process <br />-         The knowledge of the process model as a key for optimizing the process performance <br />From the physical sytem to the mathematical model <br />-         Continuous systems models of continuous industrial processes <br />-         Discrete systems models of deterministic and stochastic discrete processes <br />-         Time response and frequency response of linear systems; the exercises are carried out using the   Matlab environment.<br />-          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. <br />-         Dynamical models of the most important electronic devices for industrial applications <br />Linear analisys of dynamical systems about the equilibrium point <br />-         Frequency analysis and Laplace transform; the exercises are carried out using the Simulink environment.<br />-         Open loop and closed loop systems: the impact of the negative feedback on the closed loop dynamical behaviour <br />-         Simple and asymptotic stability : Nyquist and Bode criteria ; the rootlocus method . Some exercises are carried out using the TFI tool   included in  Matlab   <br />-         Transport delays in the loop and their effects on the stability margins. <br />Industrial simulators and their applications in process management <br />-         Discrete system simulators for designing production chains   <br />-         Replica simulators for crew training and for in-factory testing of the control devices<br />-         Real time and accelerated time simulators for diagnostic purposes. <br />-         Real time and accelerated time simulators for optimizing processes and for mitigating the consequences of unespected contingencies <br />Process control and automation <br />-         Continuous and discrete control systems : PID controllers, finite states automata, PLC based controllers. <br />-         Designing the plant automation taking into account the dynamical model of the process.<br />-         Human factors in process control : behavioural models, the Rasmussen¿s cognitive model <br />-         Case studies of    industrial   automation <br /> <br /> 

Full programme

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Bibliography

<br /> Cavallaro A., Setola R., Vasca F. :Guida operativa a Matlab, Simulink e Control Toolbox, Liguori ed , 2000 <br /> Marro G. : Controlli Automatici V ed. , Zanichelli, 2004<br /> Carlucci D. : Teoria dei Sistemi ad Eventi Discreti, UTET 1998 <br /> Bridger R. S. : Introduction to Ergonomics , Taylor & Francis , II ed. , 2003<br /> Veronesi M. : Regolazione PID, Franco Angeli, 2006 <br /> Balduzzi F., Calafiore G. : Esercizi di Automazione , UTET, 2000 <br /> Shinners S. M. : Advanced Modern Control System Theory and Design ,John Wiley & Sons, Inc , 1998 <br /> 

Teaching methods

<br />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.   <br /> 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.<br />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.  <br />

Assessment methods and criteria

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Other information

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