Minimum Violation Control Synthesis on Cyber-Physical Systems under Attacks
August 31, 2018 ยท Declared Dead ยท ๐ IEEE Conference on Decision and Control
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Luyao Niu, Jie Fu, Andrew Clark
arXiv ID
1809.00975
Category
eess.SY: Systems & Control (EE)
Cross-listed
cs.RO
Citations
7
Venue
IEEE Conference on Decision and Control
Last Checked
2 months ago
Abstract
Cyber-physical systems are conducting increasingly complex tasks, which are often modeled using formal languages such as temporal logic. The system's ability to perform the required tasks can be curtailed by malicious adversaries that mount intelligent attacks. At present, however, synthesis in the presence of such attacks has received limited research attention. In particular, the problem of synthesizing a controller when the required specifications cannot be satisfied completely due to adversarial attacks has not been studied. In this paper, we focus on the minimum violation control synthesis problem under linear temporal logic constraints of a stochastic finite state discrete-time system with the presence of an adversary. A minimum violation control strategy is one that satisfies the most important tasks defined by the user while violating the less important ones. We model the interaction between the controller and adversary using a concurrent Stackelberg game and present a nonlinear programming problem to formulate and solve for the optimal control policy. To reduce the computation effort, we develop a heuristic algorithm that solves the problem efficiently and demonstrate our proposed approach using a numerical case study.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
๐ Similar Papers
In the same crypt โ Systems & Control (EE)
R.I.P.
๐ป
Ghosted
R.I.P.
๐ป
Ghosted
Incremental Gradient, Subgradient, and Proximal Methods for Convex Optimization: A Survey
R.I.P.
๐ป
Ghosted
Wireless Network Design for Control Systems: A Survey
R.I.P.
๐ป
Ghosted
Learning-based Model Predictive Control for Safe Exploration
R.I.P.
๐ป
Ghosted
Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function
R.I.P.
๐ป
Ghosted
Novel Multidimensional Models of Opinion Dynamics in Social Networks
Died the same way โ ๐ป Ghosted
R.I.P.
๐ป
Ghosted
Language Models are Few-Shot Learners
R.I.P.
๐ป
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
๐ป
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
๐ป
Ghosted