activity
20232026
collaborators

5 papers

eess.SY2026

Input-to-state Stable Approximate Nonlinear Model Predictive Control with Realtime Feasibility

Jan Olucak, Torbjørn Cunis

In this paper, a computationally lightweight approximate robust nonlinear model predictive control (NMPC) law is proposed based on a pair of input-to-state control Lyapunov functio…

math.OC2026

On the Practical Implementation of a Sequential Quadratic Programming Algorithm for Nonconvex Sum-of-squares Problems

Jan Olucak, Torbjørn Cunis

Sum-of-squares (SOS) optimization provides a computationally tractable framework for certifying polynomial nonnegativity. If the considered problem is convex, the SOS problem can b…

math.OC2025

Safe-by-Design: Approximate Nonlinear Model Predictive Control with Real Time Feasibility

Jan Olucak, Arthur Castello B. de Oliveira, Torbjørn Cunis

This paper proposes a computationally lightweight, continuous-time receding-horizon nonlinear model predictive control (MPC) approach with infinitesimal prediction horizon. Unlike…

math.OC2024

CaΣoS: A nonlinear sum-of-squares optimization suite

Torbjørn Cunis, Jan Olucak

We present CaoS, the first MATLAB software specifically designed for nonlinear sum-of-squares optimization. A symbolic polynomial algebra system allows to formulate parametrized…

eess.SY2023

Real-time Nonlinear Model Predictive Control using One-step Optimizations and Reachable Sets

Jan Olucak, Walter Fichter, Torbjørn Cunis

Model predictive control allows solving complex control tasks with control and state constraints. However, an optimal control problem must be solved in real-time to predict the fut…