# Sound and Automated Synthesis of Digital Stabilizing Controllers for Continuous Plants

arXiv: https://arxiv.org/abs/1610.04761 · HTML: https://mlsanity.com/paper/1610.04761/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 Oct 2016.

## Built on by (most cited first, 2 of 2)

- [CEG4N: Counter-Example Guided Neural Network Quantization Refinement](https://mlsanity.com/paper/2207.04231/) (2022)
- [Formal Policy Learning from Demonstrations for Reachability Properties](https://mlsanity.com/paper/1903.00589/) (2019)

## Abstract (arXiv)

Modern control is implemented with digital microcontrollers, embedded within a dynamical plant that represents physical components. We present a new algorithm based on counter-example guided inductive synthesis that automates the design of digital controllers that are correct by construction. The synthesis result is sound with respect to the complete range of approximations, including time discretization, quantization effects, and finite-precision arithmetic and its rounding errors. We have implemented our new algorithm in a tool called DSSynth, and are able to automatically generate stable controllers for a set of intricate plant models taken from the literature within minutes.