This course aims to provide an overview on the intelligent monitoring and control methodologies for systems. Among the topics that will be covered are systems theory, control design, estimation, and approximation-based control. The main objective of the course is to familiarize students with the fundamental tools for designing monitoring and control algorithms. The application of such intelligent algorithms in energy-demanding or resource-demanding systems such as renewable energy systems, industrial processes, built environment, transportation, etc. can provide a roadmap towards the de-carbonization and sustainability of the aforementioned sectors.

Learning Outcomes

Upon completion of the course, course participants should:

• Be able to mathematically model dynamical systems
• Be able to model and design state-space domain
• Be able to design control systems
• Be able to evaluate stability, controllability and observability of dynamical systems
• Be able to design monitoring schemes for estimation
• Understand approximation theory and approximation techniques (such as Neural Networks and Radial Basis Functions)
• Be able to design adaptive parameter estimation and adaptive approximation models