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20212026
most citedSequential sum-of-squares programming for analysis of nonlinear systems

6 citations · 7 across the 12 of their papers we have counts for

collaborators

13 papers

eess.SY2026

Mission-Centric Requirements Analysis of Model Predictive Control in Spacecraft Rendezvous and Proximity Operations

Nils Maier, Torbjørn Cunis, Tam W. Nguyen

Rendezvous and proximity operations (RPO) missions are commonly designed as a sequence of distinct phases each governed by its own sample time, constraint set, and cost structure,…

math.OC2026

Worst-Case Probability Bounds for Finite-Horizon Safety under Moment Uncertainty

Renato Loureiro, Torbjørn Cunis

This paper addresses the problem of estimating upper bounds on the probability that a dynamical system will enter an undesirable region at some point within a finite time horizon.…

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

Sum-of-Squares Stability Verification on Manifolds with Applications in Spacecraft Attitude Control

Fabian Geyer, Friedrich Tuttas, Walter Fichter +1

In the context of spacecraft attitude control, parametrizations such as direction vectors or quaternions are often used to avoid singularities in the attitude representation. This,…

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

Novel Multi-objective Switched Model Predictive Control with Feasibility and Stability Guarantees

Elias Niepötter, Adrian Grimm, Torbjørn Cunis

As the relevance of control systems capable of dealing with multiple objectives rises (e.g. being economic while maintaining a certain performance), multi-objective Switched Model…

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…

cs.RO2025

Virtual Target Trajectory Prediction for Stochastic Targets

Marc Schneider, Renato Loureiro, Torbjørn Cunis +1

Trajectory prediction of aerial vehicles is a key requirement in applications ranging from missile guidance to UAV collision avoidance. While most prediction methods assume determi…

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…

math.OC2023★ 1 cited

Probabilistic Region-of-Attraction Estimation with Scenario Optimization and Converse Theorems

Torbjørn Cunis

The region of attraction characterizes well-behaved and safe operation of a nonlinear system and is hence sought after for verification. In this paper, a framework for probabilisti…

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…

math.OC2022★ 6 cited

Sequential sum-of-squares programming for analysis of nonlinear systems

Torbjørn Cunis, Benoît Legat

Numerous interesting properties in nonlinear systems analysis can be written as polynomial optimization problems with nonconvex sum-of-squares problems. To solve those problems eff…

math.OC2021

Some notes on continuity in convex optimization

Torbjørn Cunis

We provide proof that the optimal value function of a convex parametrized optimization problem in Euclidean spaces is itself a convex function onto the extended real line.