Koopman-based model predictive control for nonlinear systems with bounded model uncertainty

Tube MPC for Bilinear Koopman Models using Robust Control Contraction Metrics

A robust tube model predictive control framework for nonlinear systems represented by bilinear Koopman models identified from data, which establishes recursive feasibility, robust constraint satisfaction and input-to-state stability of the closed-loop system with respect to the mismatch between the Koopman model and th...

Bilinear Koopman-Based Robust Model Predictive Control for Unknown Nonlinear Systems via Contraction Metrics

A RMPC framework for unknown nonlinear systems with general nonlinear constraints based on data-driven bilinear Koopman realizations is proposed and robust satisfaction of the original nonlinear constraints is proved by the true closed-loop trajectory, recursive feasibility, and convergence to a neighborhood of the tar...

Iterative State- and Control-Dependent Model Predictive Control: A Jacobian-Free Formulation for Constrained Nonlinear Systems

This paper presents an iterative model predictive control algorithm that stabilizes constrained nonlinear systems without evaluating a single plant derivative. By factoring the exact nonlinear dynamics into a pseudo-linear form using state- and control-dependent coefficients (SCDCs), we replace the standard nonconvex o...

Data-Driven Koopman-Based Model Predictive Control for a Three-Tank Hydraulic System

This paper presents an applied study of data-driven Model Predictive Control (MPC) based on the Koopman operator framework for a three-tank hydraulic benchmark. The central contribution is a compact, physics-informed lifting strategy: observable functions are chosen directly from Torricelli’s law governing turbulent or...

Inverse optimal control of general nonlinear systems based on adaptive dynamic programming

Robust Adaptive Koopman MPC Under Structured and Stochastic Uncertainty for Soft Continuum Robots

Soft continuum robots exhibit highly nonlinear and configuration-dependent dynamics, making accurate trajectory tracking challenging under model uncertainty and external disturbances. This paper presents an adaptive Koopman-based model predictive control (MPC) framework for a tendon-driven soft continuum robot and eval...