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Advanced Automation And Control

2012-13 Academic year

Lecturer: Giancarlo Ferrari Trecate  

Course name: Advanced Automation And Control
Course code: 504715
Degree course: Computer Engeneering
Disciplinary field of science: ING-INF/04
The course relates to:
University credits: ECTS 9
Course website: http://sisdin.unipv.it/labsisdin/teaching/courses/ails/
files/ails.php

Specific course objectives

The course is structured into two modules: Industrial Automation and Nonlinear Systems. The goal of the Industrial Automation module is to let students familiarize with basic techniques for process planning and management. In particular, methods and algorithms of management science for modelling and solving complex decision problems will be presented. The goal of the Nonlinear Systems module is to discuss methods for the analysis of nonlinear systems using tools from system and control theory. Theory will be illustrated by means of many examples from, e.g., mechanical engineering, electrical engineering and aeronautics. In addition, techniques for the synthesis of feedback regulators for nonlinear systems will be introduced.

Course programme

Industrial Automation module

  • AUTOMATION OF PRODUCTION PROCESSES. Modelling of production processes. Flexible production systems. Management science. Operations research for decision problems.
  • MATHEMATICAL PROGRAMMING FOR DECISION PROBLEMS. Modelling of decision problems: variables, cost and constraints. Basics of convex programming. Examples of decision problems including product mix, resource allocation, transport and portfolio selection problems.
  • LINEAR PROGRAMMING (LP) PROBLEMS. Geometry of LP. Fundamental theorem of LP. Algorithms for LP problems. The simplex method: phase 1 and 2. Tableau form of the simplex method. Sensitivity analysis.
  • DUALITY THEORY. Dual problems in mathematical programming: strong and weak-duality, constraints qualification for convex programming. Optimality and KKT conditions. Duality for LP and relations between primal and dual optimizers.
  • OPTIMIZATION PROBLEMS ON GRAPHS. Basics of computational complexity theory. Shortest spanning tree problem: Kruskal's algorithm. Shortest path problem: Dijkstra's and Floyd-Warshall algorithms. Flow networks: maximum flow problems and Ford-Fulkerson algorithm. Project planning: AOA models and the critical path method. PERT analysis. Dynamic programming: Bellman principle, cost-to-go and Bellman iterations. Application of dynamic programming to optimal control of finite state machines and shortest path problems.

Nonlinear Systems module

  • INTRODUCTION TO NONLINEAR PHENOMENA. Multiple equilibria, limit cycles, complex dynamics and chaos. Existence and uniqueness of state trajectories.
  • ANALYSIS OF SECOND-ORDER SYSTEMS. The phase plane: classification of equilibria. Lymit cycles and Poincaré-Bendixon theorem.
  • STABILITY THEORY. Lyapunov functions: theorems for checking stability and instability of equilibria. Global stability analysis. LaSalle theorems. Stability for time-varying systems.
  • NONLINEAR CONTROL. Methods based on Lyapunov functions. Backstepping techniques.

Course entry requirements

Basic knowledge on algorithms. System and control theory for linear systems.

Course structure and teaching

Lectures (hours/year in lecture theatre): 68
Practical class (hours/year in lecture theatre): 0
Practicals / Workshops (hours/year in lecture theatre): 0

Suggested reading materials

Recommended textbooks for Industrial Automation (AI) and Nonlinear Systems (NL) modules

W. L. Winston, M. Venkataramanan. Introduction to Mathematical Programming: Applications and Algorithm. 4th ed., Duxbury Press, 2002. (AI).

C. Vercellis. Ottimizzazione: Teoria, metodi, applicazioni. McGraw-Hill, 2008. (AI - in Italian).

J.-J. E. Slotine, W. Li. Applied nonlinear control. Prentice-Hall, 1991. (NL).

H.K. Khalil. Nonlinear systems - third edition. Prentice-Hall, 2002. (NL).

S. Sastry. Nonlinear systems - Analysis, Stability and Control. Springer-Verlag, 1999. (NL).

Testing and exams

Closed-book, closed-note written exam. Both knowledge of theory and skills in solving simple exercises will be tested.

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