Abstraction-Free Control Synthesis to Satisfy Temporal Logic Constraints under Sensor Faults and Attacks
Luyao Niu, Zhouchi Li, Andrew Clark

TL;DR
This paper presents an abstraction-free control synthesis method for complex tasks specified by Gaussian distribution temporal logic, ensuring task satisfaction under sensor faults and attacks without finite system abstraction.
Contribution
It introduces a novel fault-tolerant control barrier function approach that guarantees task satisfaction despite malicious sensor faults and attacks, without relying on system abstraction.
Findings
Guarantees almost sure satisfaction of GDTL specifications under faults and attacks.
Develops linear constraints for control inputs using fault-tolerant CBFs.
Demonstrates effectiveness through a mobile robot coordination case study.
Abstract
We study the problem of synthesizing a controller to satisfy a complex task in the presence of sensor faults and attacks. We model the task using Gaussian distribution temporal logic (GDTL), and propose a solution approach that does not rely on computing any finite abstraction to model the system. We decompose the GDTL specification into a sequence of reach-avoid sub-tasks. We develop a class of fault-tolerant finite time convergence control barrier functions (CBFs) to guarantee that a dynamical system reaches a set within finite time almost surely in the presence of malicious attacks. We use the fault-tolerant finite time convergence CBFs to guarantee the satisfaction of `reach' property. We ensure `avoid' part in each sub-task using fault-tolerant zeroing CBFs. These fault-tolerant CBFs formulate a set of linear constraints on the control input for each sub-task. We prove that if the…
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Taxonomy
TopicsFormal Methods in Verification · Gene Regulatory Network Analysis · Simulation Techniques and Applications
