26 citations · 115 across the 68 of their papers we have counts for
80 papers
Stability Analysis and Data-driven Verification via Recurrent Lyapunov Functions
Roy Siegelmann, Fernando Paganini, Enrique Mallada
Lyapunov's direct method is a cornerstone of stability and control, but it hinges on finding a Lyapunov function, a task demanding ingenuity or computation. A key difficulty is tha…
On the Limits of Sampling-Based Reachability: Geometry, Dynamics, and Sample Complexity
Jixian Liu, Ihab Tabbara, Hussein Sibai +1
Reachability analysis is central to safety-critical control, robotics, and neural network verification, but classical computational methods, such as Hamilton--Jacobi reachability a…
Decentralized Stability Certificates in IBR-Dominated Grids: The Role of the Network State
Zhimeng Wang, Sushobhan Chatterjee, Sijia Geng +2
Small-signal instabilities, such as unforced sub-synchronous oscillations (SSOs), are increasingly observed in inverter-based resource (IBR) dominated grids. While decentralized st…
Learning Reachability of Energy Storage Arbitrage
Tomás Tapia, Agustin Castellano, Enrique Mallada +1
Power systems face increasing weather-driven variability and, therefore, increasingly rely on flexible but energy-limited storage resources. Energy storage can buffer this variabil…
Data-driven Acceleration of MPC with Guarantees
Agustin Castellano, Shijie Pan, Enrique Mallada
Model Predictive Control (MPC) is a powerful framework for optimal control but can be too slow for low-latency applications. We present a data-driven framework to accelerate MPC by…
Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
Roy Siegelmann, Enrique Mallada
We propose a method for data-driven practical stabilization of nonlinear systems with provable guarantees, based on the concept of Nonparametric Chain Policies (NCPs). The approach…
Recurrent Control Barrier Functions: A Path Towards Nonparametric Safety Verification
Jixian Liu, Enrique Mallada
Ensuring the safety of complex dynamical systems often relies on Hamilton-Jacobi (HJ) Reachability Analysis or Control Barrier Functions (CBFs). Both methods require computing a fu…
Safety-Critical Control via Recurrent Tracking Functions
Jixian Liu, Enrique Mallada
This paper addresses the challenge of synthesizing safety-critical controllers for high-order nonlinear systems, where constructing valid Control Barrier Functions (CBFs) remains c…
Safe Physics-Informed Machine Learning for Dynamics and Control
Jan Drgona, Truong X. Nghiem, Thomas Beckers +6
This tutorial paper focuses on safe physics-informed machine learning in the context of dynamics and control, providing a comprehensive overview of how to integrate physical models…
Understanding the Learning Dynamics of LoRA: A Gradient Flow Perspective on Low-Rank Adaptation in Matrix Factorization
Ziqing Xu, Hancheng Min, Lachlan Ewen MacDonald +4
Despite the empirical success of Low-Rank Adaptation (LoRA) in fine-tuning pre-trained models, there is little theoretical understanding of how first-order methods with carefully c…
A Unified Analysis of Saddle Flow Dynamics: Stability and Algorithm Design
Pengcheng You, Yingzhu Liu, Enrique Mallada
This work examines the conditions for asymptotic and exponential convergence of saddle flow dynamics of convex-concave functions. First, we propose an observability-based certifica…
Invertibility of Discrete-Time Linear Systems with Sparse Inputs
Kyle Poe, Enrique Mallada, Rene Vidal
One of the fundamental problems of interest for discrete-time linear systems is whether its input sequence may be recovered given its output sequence, a.k.a. the left inversion pro…
Dissipative Gradient Descent Ascent Method: A Control Theory Inspired Algorithm for Min-max Optimization
Tianqi Zheng, Nicolas Loizou, Pengcheng You +1
Gradient Descent Ascent (GDA) methods for min-max optimization problems typically produce oscillatory behavior that can lead to instability, e.g., in bilinear settings. To address…
A Market Mechanism for a Two-stage Settlement Electricity Market with Energy Storage
Rajni Kant Bansal, Enrique Mallada, Patricia Hidalgo-Gonzalez
Electricity markets typically clear in two stages: a day-ahead market and a real-time market. In this paper, we propose market mechanisms for a two-stage multi-interval electricity…
Learning safety critics via a non-contractive binary bellman operator
Agustin Castellano, Hancheng Min, Juan Andrés Bazerque +1
The inability to naturally enforce safety in Reinforcement Learning (RL), with limited failures, is a core challenge impeding its use in real-world applications. One notion of safe…
Recurrence of Nonlinear Control Systems: Entropy and Bit Rates
Hussein Sibai, Enrique Mallada
In this paper, we introduce the notion of recurrence entropy in the context of nonlinear control systems. A set is said to be (-)recurrent if every trajectory that starts in the…
Closed-Loop Motion Planning for Differentially Flat Systems: A Time-Varying Optimization Framework
Tianqi Zheng, John W. Simpson-Porco, Enrique Mallada
Motion planning and control are two core components of the robotic autonomy stack. The standard way to combine them uses an offline/open-loop stage, planning, which designs a feasi…
Intercept Function and Quantity Bidding in Two-stage Electricity Market with Market Power Mitigation
Rajni Kant Bansal, Yue Chen, Pengcheng You +1
Electricity markets typically operate in two stages, day-ahead and real-time. Despite best efforts striving efficiency, evidence of price manipulation has called for system-level m…
Early Neuron Alignment in Two-layer ReLU Networks with Small Initialization
Hancheng Min, Enrique Mallada, René Vidal
This paper studies the problem of training a two-layer ReLU network for binary classification using gradient flow with small initialization. We consider a training dataset with wel…
A Frequency Domain Analysis of Slow Coherency in Networked Systems
Hancheng Min, Richard Pates, Enrique Mallada
Network coherence generally refers to the emergence of simple aggregated dynamical behaviours, despite heterogeneity in the dynamics of the subsystems that constitute the network.…
Market Power Mitigation in Two-stage Electricity Market with Supply Function and Quantity Bidding
Rajni Kant Bansal, Yue Chen, Pengcheng You +1
The main goal of a sequential two-stage electricity market -- e.g., day-ahead and real-time markets -- is to operate efficiently. However, the price difference across stages due to…
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…