A computationally efficient robust model predictive control framework for uncertain nonlinear systems -- extended version

Understand

In this paper, we present a nonlinear robust model predictive control (MPC) framework for general (state and input dependent) disturbances.

• This approach uses an online constructed tube in order to tighten the nominal (state and input) constraints.
• To facilitate an efficient online implementation, the shape of the tube is based on an offline computed incremental Lyapunov function with a corresponding (nonlinear) incrementally stabilizing feedback.
• Crucially, the online optimization only implicitly includes these nonlinear functions in terms of scalar bounds, which enables an efficient implementation.