6 papers
Koopman operator theory: fundamentals, control, and applications
Igor MeziÄ, Jorge Cortés, Karl Worthmann +2
The Koopman operator has gained considerable attention due to its ability to provide a global linear representation of highly complex dynamical systems. The operator describes nonl…
Competition, stability, and functionality in excitatory-inhibitory neural circuits
Simone Betteti, William Retnaraj, Alexander Davydov +2
Energy-based models have become a central paradigm for understanding computation and stability in both theoretical neuroscience and machine learning. However, the energetic framewo…
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…
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…
On the Exponential Stability of Koopman Model Predictive Control
Xu Shang, Jorge Cortés, Yang Zheng
Koopman Model Predictive Control (MPC) uses a lifted linear predictor to efficiently handle constrained nonlinear systems. While constraint satisfaction and (practical) asymptotic…
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…