Arithmetic-Geometric Mean Robustness for Control from Signal Temporal Logic Specifications
This work addresses monitoring and control synthesis for dynamical systems, but it appears incremental as it builds on existing STL robustness methods.
The authors tackled the problem of evaluating and controlling dynamical systems under Signal Temporal Logic (STL) constraints by introducing a new average-based robustness score that highlights frequency and robustness of satisfaction, showing it provides a better score for specification satisfaction through case studies.
We present a new average-based robustness score for Signal Temporal Logic (STL) and a framework for optimal control of a dynamical system under STL constraints. By averaging the scores of different specifications or subformulae at different time points, our new definition highlights the frequency of satisfaction, as well as how robustly each specification is satisfied at each time point. We show that this definition provides a better score for how well a specification is satisfied. Its usefulness in monitoring and control synthesis problems is illustrated through case studies.