94 citations · 391 across the 65 of their papers we have counts for
13 papers · 1 filter
Data-driven Distributed and Localized Model Predictive Control
Carmen Amo Alonso, Fengjun Yang, Nikolai Matni
Motivated by large-scale but computationally constrained settings, e.g., the Internet of Things, we present a novel data-driven distributed control algorithm that is synthesized di…
Adversarially Robust Stability Certificates can be Sample-Efficient
Thomas T. C. K. Zhang, Stephen Tu, Nicholas M. Boffi +2
Motivated by bridging the simulation to reality gap in the context of safety-critical systems, we consider learning adversarially robust stability certificates for unknown nonlinea…
Generalization Bounded Implicit Learning of Nearly Discontinuous Functions
Bibit Bianchini, Mathew Halm, Nikolai Matni +1
Inspired by recent strides in empirical efficacy of implicit learning in many robotics tasks, we seek to understand the theoretical benefits of implicit formulations in the face of…
System Level Synthesis-based Robust Model Predictive Control through Convex Inner Approximation
Shaoru Chen, Nikolai Matni, Manfred Morari +1
We propose a robust model predictive control (MPC) method for discrete-time linear time-invariant systems with norm-bounded additive disturbances and model uncertainty. In our meth…
Learning Robust Output Control Barrier Functions from Safe Expert Demonstrations
Lars Lindemann, Alexander Robey, Lejun Jiang +3
This paper addresses learning safe output feedback control laws from partial observations of expert demonstrations. We assume that a model of the system dynamics and a state estima…
Adversarial Tradeoffs in Robust State Estimation
Thomas T. C. K. Zhang, Bruce D. Lee, Hamed Hassani +1
Adversarially robust training has been shown to reduce the susceptibility of learned models to targeted input data perturbations. However, it has also been observed that such adver…
Distributed and Localized Model Predictive Control. Part I: Synthesis and Implementation
Carmen Amo Alonso, Jing Shuang Li, James Anderson +1
The increasing presence of large-scale distributed systems highlights the need for scalable control strategies where only local communication is required. Moreover, in safety-criti…
Communication Topology Co-Design in Graph Recurrent Neural Network Based Distributed Control
Fengjun Yang, Nikolai Matni
When designing large-scale distributed controllers, the information-sharing constraints between sub-controllers, as defined by a communication topology interconnecting them, are as…
How Are Learned Perception-Based Controllers Impacted by the Limits of Robust Control?
Jingxi Xu, Bruce Lee, Nikolai Matni +1
The difficulty of optimal control problems has classically been characterized in terms of system properties such as minimum eigenvalues of controllability/observability gramians. W…
STL Robustness Risk over Discrete-Time Stochastic Processes
Lars Lindemann, Nikolai Matni, George J. Pappas
We present a framework to interpret signal temporal logic (STL) formulas over discrete-time stochastic processes in terms of the induced risk. Each realization of a stochastic proc…
Robust Distributed and Localized Model Predictive Control
Carmen Amo Alonso, Jing Shuang Li, Nikolai Matni +1
We present a robust Distributed and Localized Model Predictive Control (rDLMPC) framework for large-scale structured linear systems. The proposed algorithm uses the System Level Sy…
On the Sample Complexity of Stability Constrained Imitation Learning
Stephen Tu, Alexander Robey, Tingnan Zhang +1
We study the following question in the context of imitation learning for continuous control: how are the underlying stability properties of an expert policy reflected in the sample…
Learning Robust Hybrid Control Barrier Functions for Uncertain Systems
Alexander Robey, Lars Lindemann, Stephen Tu +1
The need for robust control laws is especially important in safety-critical applications. We propose robust hybrid control barrier functions as a means to synthesize control laws t…