# Robust Control Policies given Formal Specifications in Uncertain Environments

## TL;DR

This paper presents a method for synthesizing robust control policies for linear systems with complex temporal logic specifications under uncertain disturbances, ensuring specifications are met despite environmental uncertainties.

## Contribution

It introduces an affine disturbance feedback approach and formulates the control synthesis as a bilinear optimization problem with a mixed-integer quadratic program for robustness.

## Key findings

- Successfully applied to autonomous driving scenario
- Ensures specification satisfaction under all considered disturbances
- Provides a computationally feasible solution using existing solvers

## Abstract

We consider robust control synthesis for linear systems with complex specifications that are affected by uncertain disturbances. This work is motivated by autonomous systems interacting with partially known, time-varying environments. Given a specification in bounded linear temporal logic, we propose a method to synthesize control policies that fulfill the specification for all considered disturbances, where the disturbances affect the atomic propositions of the specification. Our approach relies on introducing affine disturbance feedback policies and casting the problem as a bilinear optimization problem. We introduce an inner approximation of the constraint set leading to a mixed-integer quadratic program that can be solved using general-purpose solvers. The framework is demonstrated on a numerical case study with applications to autonomous driving.