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Found 11 papers, 2 papers with code
Synthesizing Controller for Safe Navigation using Control Density Function
One of the main advantages of the proposed QP using CDF compared to QP formulated using CBF is that both the convergence/stability and safety can be combined and imposed using the CDF.
Spectral Koopman Method for Identifying Stability Boundary
For a dynamical system with an asymptotically stable equilibrium point, the domain of attraction constitutes a region consisting of all initial conditions attracted to the equilibrium point.
Data-Driven Convex Approach to Off-road Navigation via Linear Transfer Operators
We provide a convex formulation to the off-road navigation problem by lifting the problem to the density space using the linear Perron-Frobenius (P-F) operator.
Information-Theoretic Approach for Model Reduction Over Finite Time Horizon
Hence, in this paper, we propose a generalization of KL divergence-based metric called n-step KL rate metric, which could be used to compare models over a finite time horizon.
Data-driven Identification of Nonlinear Power System Dynamics Using Output-only Measurements
The developed method of Extended Subspace Identification (ESI) is suitable for systems with output measurements when all the dynamics states are not observable.
Sparse Control Synthesis for Uncertain Responsive Loads with Stochastic Stability Guarantees
Detailed numerical studies are carried out on IEEE 39-bus system to demonstrate the closed-loop stochastic stabilizing performance of the sparse controllers in enhancing frequency response under load uncertainties; as well as illustrate the fundamental trade-off between the allowable uncertainties and optimal control efforts.
Deep Learning of Koopman Representation for Control
The OpenAI Gym environment, employed for Reinforcement Learning-based control design, is used for data generation and learning of Koopman operator in control setting.
A Convex Approach to Data-driven Optimal Control via Perron-Frobenius and Koopman Operators
We provide a convex formulation for the optimal control problem of the nonlinear system.
Optimization and Control Systems and Control Systems and Control Dynamical Systems
Information Based Data-Driven Characterization of Stability and Influence in Power Systems
In this paper, we provide a purely data-driven technique for small-signal stability classification (voltage or angle stability) and influence characterization for a power network.
A Fast Saddle-Point Dynamical System Approach to Robust Deep Learning
Under the assumptions that the cost function is convex and uncertainties enter concavely in the robust learning problem, we analytically show that our algorithm converges asymptotically to the robust optimal solution under a general adversarial budget constraints as induced by $\ell_p$ norm, for $1\leq p\leq \infty$.
Particle Clustering Machine: A Dynamical System Based Approach
In this work, we propose a novel method to cluster the data points using dynamical systems theory.
