Data-Efficient Koopman Tracking MPC for Nonlinear Systems: A Kernel-Based Approach
This paper presents a data-efficient Koopman-based tracking model predictive control (MPC) scheme for nonlinear systems. Linear surrogate models are constructed online via a kernel extended dynamic mode decomposition (EDMD) framework in a reproducing kernel Hilbert space (RKHS), for which a proportional approximation e...