This summer school will focus on large-scale optimization and its applications in the control and operation of the infrastructure networks, in particular it will build comprehensive framework from theory to their specific applications for doctoral candidates.
In this summer school, we target to provide an overview of the different principles and practices that can be found under the umbrella term of Open Science. These practices span the research cycle starting from idea to outcomes including the development of software, hardware and data sharing.
Provides the students with basic notions and tools for the analysis and control of dynamic systems. Shows them how to design controllers and analyze the performance of controlled systems.
Provide an introduction to the theory and practice of Model Predictive Control (MPC). Main benefits of MPC: flexible specification of time-domain objectives, performance optimization of highly complex multivariable systems and ability to explicitly enforce constraints on system behavior.