most citedA Model Predictive Control Framework for Improving Risk-Tolerance of Manufacturing Systems

1 citations · 1 across the 5 of their papers we have counts for

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5 papers

cs.SE2024

Constrained LTL Specification Learning from Examples

Changjian Zhang, Parv Kapoor, Ian Dardik +4

Temporal logic specifications play an important role in a wide range of software analysis tasks, such as model checking, automated synthesis, program comprehension, and runtime mon…

eess.SY2024

Tolerance of Reinforcement Learning Controllers against Deviations in Cyber Physical Systems

Changjian Zhang, Parv Kapoor, Eunsuk Kang +5

Cyber-physical systems (CPS) with reinforcement learning (RL)-based controllers are increasingly being deployed in complex physical environments such as autonomous vehicles, the In…

eess.SY2024

Safe Planning through Incremental Decomposition of Signal Temporal Logic Specifications

Parv Kapoor, Eunsuk Kang, Romulo Meira-Goes

Trajectory planning is a critical process that enables autonomous systems to safely navigate complex environments. Signal temporal logic (STL) specifications are an effective way t…

eess.SY2023

Safe Environmental Envelopes of Discrete Systems

Rômulo Meira-Góes, Ian Dardik, Eunsuk Kang +2

A safety verification task involves verifying a system against a desired safety property under certain assumptions about the environment. However, these environmental assumptions m…

eess.SY20231 cited

A Model Predictive Control Framework for Improving Risk-Tolerance of Manufacturing Systems

Mostafa Tavakkoli Anbarani, Efe C. Balta, Rômulo Meira-Góes +1

The need for control strategies that can address dynamic system uncertainty is becoming increasingly important. In this work, we propose a Model Predictive Control by quantifying t…