# Model Predictive Control for Signal Temporal Logic Specification

arXiv: https://arxiv.org/abs/1703.09563 · HTML: https://mlsanity.com/paper/1703.09563/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Mar 2017.

## Built on by (most cited first, 8 of 8)

- [Deep reinforcement learning under signal temporal logic constraints using Lagrangian relaxation](https://mlsanity.com/paper/2201.08504/) (2022)
- [Follow The Rules: Online Signal Temporal Logic Tree Search for Guided Imitation Learning in Stochastic Domains](https://mlsanity.com/paper/2209.13737/) (2022)
- [Learning Minimally-Violating Continuous Control for Infeasible Linear Temporal Logic Specifications](https://mlsanity.com/paper/2210.01162/) (2022)
- [Neural Network-based Control for Multi-Agent Systems from Spatio-Temporal Specifications](https://mlsanity.com/paper/2104.02737/) (2021)
- [Learning-'N-Flying: A Learning-based, Decentralized Mission Aware UAS Collision Avoidance Scheme](https://mlsanity.com/paper/2101.10404/) (2021)
- [Risk-Awareness in Learning Neural Controllers for Temporal Logic Objectives](https://mlsanity.com/paper/2210.07439/) (2022)
- [Reinforcement Learning Agent Training with Goals for Real World Tasks](https://mlsanity.com/paper/2107.10390/) (2021)
- [CatlNet: Learning Communication and Coordination Policies from CaTL+ Specifications](https://mlsanity.com/paper/2212.11792/) (2022)

## Abstract (arXiv)

We present a mathematical programming-based method for model predictive control of cyber-physical systems subject to signal temporal logic (STL) specifications. We describe the use of STL to specify a wide range of properties of these systems, including safety, response and bounded liveness. For synthesis, we encode STL specifications as mixed integer-linear constraints on the system variables in the optimization problem at each step of a receding horizon control framework. We prove correctness of our algorithms, and present experimental results for controller synthesis for building energy and climate control.