7 papers
Control Forward-Backward Consistency: Quantifying the Accuracy of Koopman Control Family Models
Masih Haseli, Jorge Cortés, Joel W. Burdick
This paper extends the forward-backward consistency index, originally introduced in Koopman modeling of systems without input, to the setting of control systems, providing a closed…
Real-Time Learning of Predictive Dynamic Obstacle Models for Robotic Motion Planning
Stella Kombo, Masih Haseli, Skylar X. Wei +1
Autonomous systems often must predict the motions of nearby agents from partial and noisy data. This paper asks and answers the question: "can we learn, in real-time, a nonlinear p…
On the Existence of Koopman Linear Embeddings for Controlled Nonlinear Systems
Xu Shang, Masih Haseli, Jorge Cortés +1
Koopman linear representations have become a popular tool for control design of nonlinear systems, yet it remains unclear when such representations are exact. In this paper, we est…
Two Roads to Koopman Operator Theory for Control: Infinite Input Sequences and Operator Families
Masih Haseli, Igor MeziÄ, Jorge Cortés
The Koopman operator, originally defined for dynamical systems without input, has inspired many applications in control. Yet, the theoretical foundations underpinning this progress…
Modeling Nonlinear Control Systems via Koopman Control Family: Universal Forms and Subspace Invariance Proximity
Masih Haseli, Jorge Cortés
This paper introduces the Koopman Control Family (KCF), a mathematical framework for modeling general (not necessarily control-affine) discrete-time nonlinear control systems with…
Koopman Operators in Robot Learning
Lu Shi, Masih Haseli, Giorgos Mamakoukas +5
Koopman operator theory offers a rigorous treatment of dynamics and has been emerging as an alternative modeling and learning-based control method across various robotics sub-domai…