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Digital archive of theses discussed at the University of Pisa

 

Thesis etd-05102022-103315


Thesis type
Tesi di dottorato di ricerca
Author
DINI, PIERPAOLO
URN
etd-05102022-103315
Thesis title
Model-Based Design of Embedded Control & Monitoring Algorithms for Advanced Mechatronic Systems
Academic discipline
ING-INF/01
Course of study
SMART INDUSTRY
Supervisors
tutor Prof. Saponara, Sergio
tutor Pierini, Marco
Keywords
  • automation
  • automotive
  • control
  • industry
  • mechatronics
  • power systems
Graduation session start date
11/06/2022
Availability
Withheld
Release date
11/06/2092
Summary
The research project aims to apply and improve a systematic design approach to automatic control systems and supervisory and monitoring algorithms for increasingly complex modern mechatronic processes.
Chapter 1 addresses the problem of mitigating the effects of cogging torque in permanent magnet synchronous motors.
In Chapter 2, the use of an extended Kalman filter (EKF) in the continuous-time domain is presented, discussing the advantages of an observer design based on a dynamic motor model in three-phase, direct-quadrature axes.
In Chapter 3, a development method based on model-based design, co-simulation and formal verification is introduced.
In Chapter 4, the use of the GRAMPC library is proposed for the implementation of an embedded platform of a control algorithm for assisted driving that includes the function of avoiding obstacles along the road.
Chapter 5 presents the workflow for the design and verification of the electrical and thermal behaviour and the validation of the control algorithms, for an On-Board Charger (OBC), through a Model-Based Design (MBD) approach.
Chapters 6 and 7 it is shown the design, implementation and experimental evaluation of the Intrusion Detection System (IDS) based on voltage fingerprinting and artificial intelligence.
Chapter 8 it is presented the application of different machine-learning models to the problem of anomaly classification in the context of local area network (LAN) traffic analysis.
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