# A Framework for Output-Feedback Symbolic Control

arXiv: https://arxiv.org/abs/2011.14848 · HTML: https://mlsanity.com/paper/2011.14848/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Nov 2020.

## Built on by (most cited first, 1 of 1)

- [SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning](https://mlsanity.com/paper/2502.15512/) (2025)

## Abstract (arXiv)

Symbolic control is an abstraction-based controller synthesis approach that provides, algorithmically, certifiable-by-construction controllers for cyber-physical systems. Symbolic control approaches usually assume that full-state information is available which is not suitable for many real-world applications with partially-observable states or output information. This article introduces a framework for output-feedback symbolic control. We propose relations between original systems and their symbolic models based on outputs. They enable designing symbolic controllers and refining them to enforce complex requirements on original systems. We provide example methodologies to synthesize and refine output-feedback symbolic controllers.