Model-Based Design of Embedded Control & Monitoring Algorithms for Advanced Mechatronic Systems

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.