Mazen Alamir is Research Director at CNRS, France. He graduated in mechanics (Grenoble, 1990) and avionics (Toulouse 1992). He received his Ph.D. in nonlinear model predictive control in 1995 from Grenoble Institute of Technology. He served as Head of the nonlinear systems and complexity research group at the Control System Department, University of Grenoble-Alpes. His main research topics are nonlinear model predictive control, nonlinear moving-horizon estimators and blind anomaly detection in engineering equipments. He was Member of the IFAC technical committee on nonlinear systems as well as the IEEE Conference Editorial Board and served as Associate Editor of the IEEE Transactions on Automatic Control (2008-2021). He organized the first IFAC workshop on NMPC for Fast Systems, Grenoble 2006. He is Co-Founder and Scientific Advisor of the startup Amiral-Technologies, specialized in AI algorithms for industrial predictive maintenance and diagnosis, and Winner of the 2017 GE-digital industrial challenge.

• Part I: Definitions, Notation, Concepts and Tools.- What is this Book About?.- Definitions, Notation and Main Concepts.- Quick Python Reminders and Key Modules.- Part II: Methodologies and Algorithms.- Handling Uncertainties via Standard Methods.- Solving Deterministic Model Predictive Control Problems.- A Framework and a Python-Package for Real-Time Nonlinear Model Predictive Control Parameters Settings.- Designing an Uncertainty-Aware Dynamic Output Feedback via Deterministic Optimal Control Solutions.- Nonlinear Moving Horizon Extended Observers.- Further Advanced Topics.- Control of Automotive Automated Manual Transmission.- Power Management in an EV-Charging Station.- Feedback Law with Probabilistic Certification for Propofol-Based Control of BIS During Anesthesia.- Learning Optimal Energy Management in Hybrid Vehicles.- Q-Learning Solution to the Combined Therapy of Cancer.- Decentralized Frequency Control in Micro-grids.

Mazen Alamir is Research Director at CNRS, France. He graduated in mechanics (Grenoble, 1990) and avionics (Toulouse 1992). He received his Ph.D. in nonlinear model predictive control in 1995 from Grenoble Institute of Technology. He served as Head of the nonlinear systems and complexity research group at the Control System Department, University of Grenoble-Alpes. His main research topics are nonlinear model predictive control, nonlinear moving-horizon estimators and blind anomaly detection in engineering equipments. He was Member of the IFAC technical committee on nonlinear systems as well as the IEEE Conference Editorial Board and served as Associate Editor of the IEEE Transactions on Automatic Control (2008-2021). He organized the first IFAC workshop on NMPC for Fast Systems, Grenoble 2006. He is Co-Founder and Scientific Advisor of the startup Amiral-Technologies, specialized in AI algorithms for industrial predictive maintenance and diagnosis, and Winner of the 2017 GE-digital industrial challenge.

• Part I: Definitions, Notation, Concepts and Tools.- What is this Book About?.- Definitions, Notation and Main Concepts.- Quick Python Reminders and Key Modules.- Part II: Methodologies and Algorithms.- Handling Uncertainties via Standard Methods.- Solving Deterministic Model Predictive Control Problems.- A Framework and a Python-Package for Real-Time Nonlinear Model Predictive Control Parameters Settings.- Designing an Uncertainty-Aware Dynamic Output Feedback via Deterministic Optimal Control Solutions.- Nonlinear Moving Horizon Extended Observers.- Further Advanced Topics.- Control of Automotive Automated Manual Transmission.- Power Management in an EV-Charging Station.- Feedback Law with Probabilistic Certification for Propofol-Based Control of BIS During Anesthesia.- Learning Optimal Energy Management in Hybrid Vehicles.- Q-Learning Solution to the Combined Therapy of Cancer.- Decentralized Frequency Control in Micro-grids.

Mazen Alamir is Research Director at CNRS, France. He graduated in mechanics (Grenoble, 1990) and avionics (Toulouse 1992). He received his Ph.D. in nonlinear model predictive control in 1995 from Grenoble Institute of Technology. He served as Head of the nonlinear systems and complexity research group at the Control System Department, University of Grenoble-Alpes. His main research topics are nonlinear model predictive control, nonlinear moving-horizon estimators and blind anomaly detection in engineering equipments. He was Member of the IFAC technical committee on nonlinear systems as well as the IEEE Conference Editorial Board and served as Associate Editor of the IEEE Transactions on Automatic Control (2008-2021). He organized the first IFAC workshop on NMPC for Fast Systems, Grenoble 2006. He is Co-Founder and Scientific Advisor of the startup Amiral-Technologies, specialized in AI algorithms for industrial predictive maintenance and diagnosis, and Winner of the 2017 GE-digital industrial challenge.

• Part I: Definitions, Notation, Concepts and Tools.- What is this Book About?.- Definitions, Notation and Main Concepts.- Quick Python Reminders and Key Modules.- Part II: Methodologies and Algorithms.- Handling Uncertainties via Standard Methods.- Solving Deterministic Model Predictive Control Problems.- A Framework and a Python-Package for Real-Time Nonlinear Model Predictive Control Parameters Settings.- Designing an Uncertainty-Aware Dynamic Output Feedback via Deterministic Optimal Control Solutions.- Nonlinear Moving Horizon Extended Observers.- Further Advanced Topics.- Control of Automotive Automated Manual Transmission.- Power Management in an EV-Charging Station.- Feedback Law with Probabilistic Certification for Propofol-Based Control of BIS During Anesthesia.- Learning Optimal Energy Management in Hybrid Vehicles.- Q-Learning Solution to the Combined Therapy of Cancer.- Decentralized Frequency Control in Micro-grids.