Results 281 to 290 of about 1,082,543 (312)

KOROL: Learning Visualizable Object Feature with Koopman Operator Rollout for Manipulation

Conference on Robot Learning
Learning dexterous manipulation skills presents significant challenges due to complex nonlinear dynamics that underlie the interactions between objects and multi-fingered hands.
Hongyi Chen, Abulikemu Abuduweili, Aviral Agrawal, Yunhai Han, H. Ravichandar, Changliu Liu, Jeffrey Ichnowski   +6 more
semanticscholar   +1 more source

Data-Driven Control Synthesis Using Koopman Operator: A Robust Approach

American Control Conference
This paper presents a data-driven control design method for nonlinear systems using the Koopman operator framework. The Koopman operator lifts nonlinear dynamics to a higher-dimensional space, where observable functions evolve linearly.
Mert Eyüboğlu, Nathan Powell, Alireza Karimi   +2 more
semanticscholar   +1 more source

Koopman operator based nonlinear dynamic textures

2015 American Control Conference (ACC), 2015
Dynamic texture (DT) is a simple yet powerful paradigm to model videos with repetitive spatiotemporal behavior. In this paper we propose a novel nonlinear approach for modeling complex DTs based on Koopman operator theoretic method. Koopman operator is linear but infinite dimensional operator, and captures full nonlinear behavior.
openaire   +1 more source

Resilient Formation Control With Koopman Operator for Networked NMRs Under Denial-of-Service Attacks

IEEE Transactions on Systems, Man, and Cybernetics: Systems
This article presents a resilient formation control framework for networked nonholonomic mobile robots (NMRs) that enables long-time recovery abilities subject to denial-of-service (DoS) attacks by taking advantage of the Koopman operator.
Weiwei Zhan, Zhiqiang Miao, Hui Zhang, Yanjie Chen, Zhengguang Wu, Wei He, Yaonan Wang   +6 more
semanticscholar   +1 more source

Learning Noise-Robust Stable Koopman Operator for Control With Hankel DMD

IEEE Transactions on Control Systems Technology
We propose a noise-robust learning framework for the Koopman operator of nonlinear dynamical systems, with guaranteed long-term stability and improved model performance for better model-based predictive control tasks. Unlike some existing approaches that
Shahriar Akbar Sakib, Shaowu Pan
semanticscholar   +1 more source

Performance-Oriented Data-Driven Control: Fusing Koopman Operator and MPC-Based Reinforcement Learning

IEEE Control Systems Letters
This letter develops the machinery of Koopman-based Model Predictive Control (KMPC) design, where the Koopman derived model is unable to capture the real nonlinear system perfectly.
Hossein Nejatbakhsh Esfahani, Umesh Vaidya, Javad Mohammadpour Velni   +2 more
semanticscholar   +1 more source

Data-driven optimal control of unknown nonlinear dynamical systems using the Koopman operator

Conference on Learning for Dynamics & Control
Nonlinear optimal control is vital for numerous applications but remains challenging for unknown systems due to the difficulties in accurately modelling dynamics and handling computational demands, particularly in high-dimensional settings.
Zhexuan Zeng, Rui Zhou, Yiming Meng, Jun Liu   +3 more
semanticscholar   +1 more source

On the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions

Chaos
This work explores the relationship between state space methods and Koopman operator-based methods for predicting the time evolution of nonlinear dynamical systems. We demonstrate that extended dynamic mode decomposition with dictionary learning (EDMD-DL)
Jake Buzhardt, Ricardo Constante-Amores, Michael D. Graham   +2 more
semanticscholar   +1 more source

Data-Driven Koopman Operator-Based Error-State Kalman Filter for Enhanced State Estimation of Quadrotors in Agile Flight

IEEE/RJS International Conference on Intelligent RObots and Systems
Highly dynamic maneuvers pose a challenge to conventional state estimators of quadrotors in rapidly tracking the pose. This paper proposes a data-driven Koopman operator-based error-state Kalman filter (K-ESKF) to enhance pose estimation in agile flight.
Peng Huang, Ketong Zheng, Gerhard Fettweis   +2 more
semanticscholar   +1 more source

Koopman Transformers: Koopman operator deep learning via attention

2023
openaire   +1 more source