CONTROL TECHNIQUES
Academic year and teacher
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- Versione italiana
- Academic year
- 2011/2012
- Teacher
- SILVIO SIMANI
- Credits
- 6
- Curriculum
- INDUSTRIALE
- Didactic period
- Primo Semestre
- SSD
- ING-INF/04
Training objectives
- The aim of the course is to provide, by means of seminars on specific topics, basic knowledge of advanced methods and tools for Automatic Control that are used in the industry. The students will also learn Computer Aided Control System Design (CACSD) tools that are essential for their professional and academical activity.
Prerequisites
- It is expected that students attended the basic courses of Automatic Control and Digital Control Systems.
Course programme
- Neural Networks (NN): introduction, modeling, simple networkds, Adaline Perceptron, Multi Layer networks, training algorithms, Radial Basis Function networks, Genetic Algorithms for NN optimisation, system identification and control applications of NN.
Optimal Control and State Estimation: State Estimation of linear dynamic systems in deterministic and stochastic environments, Optimal Control of linear systems with finite and infinite time horizon.
Nonlinear Control Systems: nonlinear dynamic systems and Lyapounov Stability Theory, control techniques for nonlinear systems and their industrial applications, Feedback Linearization, Sliding Mode Control.
Fuzzy Logic and Fuzzy Control: basic theory of fuzzy logic, propositions and inductive inference, basic components of a fuzzy system (fuzzifier, inference engine, defuzzifier), applications of Fuzzy Logic in Automation and Control. Didactic methods
- Oral lessons and practical exercise sessions with personal computer.
Learning assessment procedures
- Written report describing a practical project solved using the computer aided design tools and oral exam concerning the issues of the course.
Reference texts
- Lesson handouts
