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There has been an increasing interest in using neural networks in closed-loop control systems to improve performance and reduce computational costs for on-line implementation.
Verification of hybrid systems via mathematical programming
Alberto Bemporad and Manfred Morari · 1999
Earlier work this paper cites.
Optimization-based verification and stability characterization of piecewise affine and hybrid systems
Alberto Bemporad, Fabio Danilo Torrisi, and Manfred Morari · 2000
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Computational techniques for the verification of hybrid systems
Claire J Tomlin, Ian Mitchell, Alexandre M Bayen, and Meeko Oishi · 2003
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Yalmip: A toolbox for modeling and optimization in matlab
Johan Lofberg · 2004
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Safety verification of hybrid systems using barrier certificates
Stephen Prajna and Ali Jadbabaie · 2004
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SNOPT: An SQP algorithm for large-scale constrained optimization
Philip E. Gill, Walter Murray, and Michael A. Saunders · 2005
Earlier work this paper cites.
Set-theoretic methods in control
Franco Blanchini and Stefano Miani · 2008
Earlier work this paper cites.
Cvx: Matlab software for disciplined convex programming, 2009
Michael Grant, Stephen Boyd, and Yinyu Ye · 2009
Earlier work this paper cites.
Multi-Parametric Toolbox 3.0
M. Herceg, M. Kvasnica, C.N. Jones, and M. Morari · 2013
Earlier work this paper cites.
Computer-aided verification of coordinating processes: the automata-theoretic approach
Robert P Kurshan · 2014
Earlier work this paper cites.
End to end learning for self-driving cars
Mariusz Bojarski, Davide Del Testa, Daniel Dworakowski, Bernhard Firner, Beat Flepp, Prasoon Goyal, Lawrence D Jackel, Mathew Monfort, Urs Muller, Jiakai Zhang, et al · 2016
Earlier work this paper cites.
Adversarial examples in the physical world
Alexey Kurakin, Ian Goodfellow, and Samy Bengio · 2016
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The limitations of deep learning in adversarial settings
Nicolas Papernot, Patrick McDaniel, Somesh Jha, Matt Fredrikson, Z Berkay Celik, and Ananthram Swami · 2016
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Learning deep control policies for autonomous aerial vehicles with mpc-guided policy search
Tianhao Zhang, Gregory Kahn, Sergey Levine, and Pieter Abbeel · 2016
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The MOSEK optimization toolbox for MATLAB manual. Version 8.1
MOSEK ApS · 2017
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Predictive control for linear and hybrid systems
Francesco Borrelli, Alberto Bemporad, and Manfred Morari · 2017
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Output range analysis for deep neural networks
Souradeep Dutta, Susmit Jha, Sriram Sanakaranarayanan, and Ashish Tiwari · 2017
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Formal verification of piece-wise linear feed-forward neural networks
Learning an approximate model predictive controller with guarantees
Michael Hertneck, Johannes Köhler, Sebastian Trimpe, and Frank Allgöwer · 2018
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Semidefinite relaxations for certifying robustness to adversarial examples
Aditi Raghunathan, Jacob Steinhardt, and Percy S Liang · 2018
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Constrained cross-entropy method for safe reinforcement learning
Min Wen and Ufuk Topcu · 2018
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Reachability analysis for neural feedback systems using regressive polynomial rule inference
Souradeep Dutta, Xin Chen, and Sriram Sankaranarayanan · 2019
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Probabilistic verification and reachability analysis of neural networks via semidefinite programming
Mahyar Fazlyab, Manfred Morari, and George J Pappas · 2019
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Ruediger Ehlers · 2017
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Safety verification of deep neural networks
Xiaowei Huang, Marta Kwiatkowska, Sen Wang, and Min Wu · 2017
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Reluplex: An efficient smt solver for verifying deep neural networks
Guy Katz, Clark Barrett, David L Dill, Kyle Julian, and Mykel J Kochenderfer · 2017
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Provable defenses against adversarial examples via the convex outer adversarial polytope
J Zico Kolter and Eric Wong · 2017
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An approach to reachability analysis for feed-forward relu neural networks
Alessio Lomuscio and Lalit Maganti · 2017
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Agile autonomous driving using end-to-end deep imitation learning
Yunpeng Pan, Ching-An Cheng, Kamil Saigol, Keuntaek Lee, Xinyan Yan, Evangelos Theodorou, and Byron Boots · 2017
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Approximating explicit model predictive control using constrained neural networks
Steven Chen, Kelsey Saulnier, Nikolay Atanasov, Daniel D Lee, Vijay Kumar, George J Pappas, and Manfred Morari · 2018
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Mahyar Fazlyab, Manfred Morari, and George J Pappas · 2019
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Efficient and accurate estimation of lipschitz constants for deep neural networks
Mahyar Fazlyab, Alexander Robey, Hamed Hassani, Manfred Morari, and George Pappas · 2019
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Reachnn: Reachability analysis of neural-network controlled systems
Chao Huang, Jiameng Fan, Wenchao Li, Xin Chen, and Qi Zhu · 2019
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Verisig: verifying safety properties of hybrid systems with neural network controllers
Radoslav Ivanov, James Weimer, Rajeev Alur, George J Pappas, and Insup Lee · 2019
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Verification of closed-loop systems with neural network controllers
Diego Manzanas Lopez, Patrick Musau, Hoang-Dung Tran, and Taylor T. Johnson · 2019
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Motion planning networks
Ahmed H Qureshi, Anthony Simeonov, Mayur J Bency, and Michael C Yip · 2019
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