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Software Development

TRUST: Stability and Safety Controller Synthesis for Unknown Dynamical Models Using a Single Trajectory

TRUST is an open-source software tool developed for data-driven controller synthesis of dynamical systems with unknown mathematical models, ensuring either stability or safety properties. By collecting only a single input-state trajectory from the unknown system and satisfying a rank condition that ensures the system is persistently excited according to the Willems et al.'s fundamental lemma, TRUST aims to design either control Lyapunov functions (CLF) or control barrier certificates (CBC), along with their corresponding stability or safety controllers. The tool implements sum-of-squares (SOS) optimization programs solely based on data to enforce stability or safety properties across four system classes: (i) continuous-time nonlinear polynomial systems, (ii) continuous-time linear systems, (iii) discrete-time nonlinear polynomial systems, and (iv) discrete-time linear systems.

TRUST also offers a Python-based web application featuring an intuitive, reactive graphic user interface (GUI) built with web technologies, which allows users to work with the application via the web without requiring downloads or installations. Leveraging the power of the Python backend and a JavaScript frontend, TRUST is designed to be highly user-friendly and accessible across desktop, laptop, tablet, and mobile devices.



Download

TRUST is an open-source tool and can be downloaded from its GitHub repository. The web application can be accessed at https://trust.tgo.dev.

Tool paper

Support

Please report any problems/bugs you face while installing and running TRUST to Amy Nejati or Abolfazl Lavaei