Emerging methodologies in stability and optimization problems of learning‐based nonlinear model predictive control: A survey
F Meng, X Shen, HR Karimi - International Journal of Circuit …, 2022 - Wiley Online Library
Since last 40 years, the theory and technology of model predictive control (MPC) have been
developed rapidly. However, nonlinear MPC still faces difficulties such as high online …
developed rapidly. However, nonlinear MPC still faces difficulties such as high online …
KPC: Learning-based model predictive control with deterministic guarantees
ET Maddalena, P Scharnhorst… - … for Dynamics and …, 2021 - proceedings.mlr.press
Abstract We propose Kernel Predictive Control (KPC), a learning-based predictive control
strategy that enjoys deterministic guarantees of safety. Noise-corrupted samples of the …
strategy that enjoys deterministic guarantees of safety. Noise-corrupted samples of the …
Adaptive learning and robust model predictive control for uncertain dynamic systems
K Zhang - 2021 - dspace.library.uvic.ca
Recent decades have witnessed the phenomenal success of model predictive control (MPC)
in a wide spectrum of domains, such as process industries, intelligent transportation …
in a wide spectrum of domains, such as process industries, intelligent transportation …