The Course of Advanced Automation and Control - Nonlinear Control Part for a.y.  2021/2022 can be found on the new platform:

Please enroll to that course to to be updated on course activities.

Process Control Course for a.y.  2021/2022 can be found on the new platform:

Please enroll to that course to be updated on course activities.

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 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 program and content

Optimization 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.

Dual Programming.

Multi-parametric Programming.

The simplex method: phase 1 and 2. Tableau form of the simplex method.
Interior Point method.

Sensitivity analysis.

MIXED-INTEGER LINEAR PROGRAMMING (MILP). The use of binary variables in optimization programs. Branch and bound algorithm.
Extension also to the case of integer variables (and not only binary)

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.

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.

Dynamic programming applied to mobile robotics.

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. Sliding Mode Control.

Teaching material

The material of the course will be available at

The lectures will be held in streaming. I will try to upload the registrations online afterwards.

Recommended textbooks (optimization part)

- W. L. Winston, M. Venkataramanan. Introduction to Mathematical Programming: Applications and Algorithm. 4th ed., Duxbury Press, 2002. 
- S Boyd L Vandenberghe , Convex Optimization, Cambridge University Press, 2004
- C. Vercellis. Ottimizzazione: Teoria, metodi, applicazioni. McGraw-Hill, 2008. (in Italian).

Robot Control Course for a.y.  2021/2022 can be found on the new platform:

Please enroll to that course to be updated on course activities.

The course introduces key principles in terms of business strategy and management. The main learning outcome of this part is the capacity to develop an industrial plan. The industrial planning will consider the major transformations occurring under an industry 4.0 scenario. 

The second part of the course will focus on entrepreneurship, how to start up a business and write a business plan and how to design the business model. 

Business finance will be the third part of the course, both from the perspective of large and established firms and from the perspective of start ups.

The learning outcomes are the necessary knowledge for a graduate in engineering to solve managerial and entrepreneurial problems in organisations in the above mentioned fields, but also the capacity to work in team and to present and discuss a project work.

Prego collegarsi alla nuova piattaforma KIRO. 

An overview of automatic machinery and the manufacturing industry world from a mechanical and mechatronic point of view.

The course is meant to provide an overview on electronics for application to industrial measurements. The main topics are signal amplification, filtering, and generation, digital circuits and Analog to Digital and Digital to Analog conversion. The course includes practical activities to be carried out in the electronic teaching laboratory. The course also aims at providing students with the needed tools to expand their knowledge of electronics beyond the course program.

The course will provide an introduction and background on the main components and techniques of a communication systems. This part will cover fundamentals of signals and transmisison over wired (cables) and wireless (radio) media. The secon part of the course will review multiple access techniques and some performance metrics. Finally, the main part of the course will be dedicated to a description of the main communication systems in the local environment as well as in the global connectivity. Among the first, emphasys will be given to local area networks, their topology and performance. Applications in industrial environments will be more specifically addressed together with exploitation of sensors to support control systems. Global coverage systems will encompass telephone networks (both fixed and mobile/cellular) and the Internet.