The Capital University of Science and Technology hosted a workshop entitled “Model Predictive Control” from 4-6th April 2019 in A-2 Auditorium. Office of Research Innovation and Commercialization (ORIC) organized the workshop aiming to equip faculty, researchers and students with the contemporary knowledge of Model Predictive Control: Alogrithms, Tools and Applications. The resource person for workshop was Dr. Amir Shahzad.
The objectives of the workshop were to present the basic introductory material, as well as more recent results, on the topics of Model Predictive Control (MPC). The workshop was intended for graduate students, researchers and practitioners, who learn the theory and practice of Model Predictive Control (MPC) for constrained LTI and LTV systems. Model Predictive Control is a tool to optimize a system’s performance by using a model to predict the system’s future trajectory. It is one of the most commonly implemented advanced control techniques in the process industries today. In recent years MPC is rapidly expanding in several other domains, such as in the automotive and aerospace industries, smart energy grids, and financial engineering. The course will make use of the MPC Toolbox for MATLAB.