# Set-Based Adaptive Safety Control

## TL;DR

This paper presents a set-theoretic adaptive safety control system for educational control labs that prevents hardware damage by ensuring system states remain within safe regions, with real-time switching to a safe mode if needed.

## Contribution

We designed a set-based adaptive safety control method integrated into Simulink for educational use, enhancing hardware safety during control system experiments.

## Key findings

- Successfully implemented real-time adaptive safety control
- Ensured system states remain within safe regions
- Provided a reusable safety control block for labs

## Abstract

Feedback Control Systems, ME C134/EE C128, is an introductory control systems course at UC Berkeley. Over the entire course, students gain practical experience by implementing various control schemes and designing observers in an effort to ultimately stabilize an inverted pendulum on a linear track. Throughout this learning process, frequent mishaps occur where improper controller implementation damages hardware. A simple example concerns the student's controller driving the cart into the wall at full speed. To offset the financial burden placed on the university in light of these mishaps, we designed a streamlined adaptive control system using set theory. We utilized lab-provided plant models to generate an $O_\infty$ set, attenuated the vertices to generate a safe, sub-region $S_\infty$, and attenuated in such a manner as to ensure an evolution of the vertices of $S_\infty$ remained within $O_\infty$ for at least one time step. Afterwards, we constructed a single Simulink block for students to easily implement within their own control schemes. This block consistently checks to see whether the system state remains within $S_\infty$. If that check is true, our controller does nothing. If it returns false, our controller takes over, drives the system to a prescribed safe-point, and shuts the system down. Overall, our process assumes perfect plant modelling, though our insistence on an evolution of $S_\infty$ remaining within $O_\infty$ resulted in considerable robustness to disturbances. In the end we were successful in implementing this real-time adaptive system and will provide it to the department for use in future labs.