26 citations · 115 across the 68 of their papers we have counts for
6 papers · 1 filter
Constrained Reinforcement Learning via Dissipative Saddle Flow Dynamics
Tianqi Zheng, Pengcheng You, Enrique Mallada
In constrained reinforcement learning (C-RL), an agent seeks to learn from the environment a policy that maximizes the expected cumulative reward while satisfying minimum requireme…
Learning Coherent Clusters in Weakly-Connected Network Systems
Hancheng Min, Enrique Mallada
We propose a structure-preserving model-reduction methodology for large-scale dynamic networks with tightly-connected components. First, the coherent groups are identified by a spe…
Spectral clustering and model reduction for weakly-connected coherent network systems
Hancheng Min, Enrique Mallada
We propose a novel model-reduction methodology for large-scale dynamic networks with tightly-connected components. First, the coherent groups are identified by a spectral clusterin…
Frequency shaping control for weakly-coupled grid-forming IBRs
Bala Kameshwar Poolla, Yashen Lin, Andrey Bernstein +2
We consider the problem of controlling the frequency of low-inertia power systems via inverter-based resources (IBRs) that are weakly connected to the grid. We propose a novel grid…
Model-free Learning of Regions of Attraction via Recurrent Sets
Yue Shen, Maxim Bichuch, Enrique Mallada
We consider the problem of learning an inner approximation of the region of attraction (ROA) of an asymptotically stable equilibrium point without an explicit model of the dynamics…
Closed-Form Minkowski Sum Approximations for Efficient Optimization-Based Collision Avoidance
James Guthrie, Marin Kobilarov, Enrique Mallada
Motion planning methods for autonomous systems based on nonlinear programming offer great flexibility in incorporating various dynamics, objectives, and constraints. One limitation…