Stability Mechanisms for Predictive Safety Filters (2404.05496v2)
Abstract: Predictive safety filters enable the integration of potentially unsafe learning-based control approaches and humans into safety-critical systems. In addition to simple constraint satisfaction, many control problems involve additional stability requirements that may vary depending on the specific use case or environmental context. In this work, we address this problem by augmenting predictive safety filters with stability guarantees, ranging from bounded convergence to uniform asymptotic stability. The proposed framework extends well-known stability results from model predictive control (MPC) theory while supporting commonly used design techniques. As a result, straightforward extensions to dynamic trajectory tracking problems can be easily adapted, as outlined in this article. The practicality of the framework is demonstrated using an automotive advanced driver assistance scenario, involving a reference trajectory stabilization problem.
- Robotics in vivo: A perspective on human–robot interaction in surgical robotics. Annual Review of Control, Robotics, and Autonomous Systems, 3(1):221–242, 2020.
- Stability and feasibility of state constrained MPC without stabilizing terminal constraints. Systems & Control Letters, 72:14–21, 2014.
- A. Agrawal and K. Sreenath. Discrete control barrier functions for safety-critical control of discrete systems with application to bipedal robot navigation. In Robotics: Science and Systems, volume 13, 1–10, Cambridge, MA, USA, 07 2017.
- On the inherent robustness of optimal and suboptimal nonlinear MPC. Systems & Control Letters, 106:68–78, 2017.
- Commonroad: Composable benchmarks for motion planning on roads. In Proc. of the IEEE Intelligent Vehicles Symposium, 2017.
- The human-in-the-loop design approach to the longitudinal automation system for an intelligent vehicle. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 40(4):708–720, 2010.
- Predictive stability filters for nonlinear dynamical systems affected by disturbances, 2024. Available: https://arxiv.org/abs/2401.11183.
- S. Elaydi. Stability Theory. Springer, New York, 2005.
- A nonlinear model predictive control framework using reference generic terminal ingredients. IEEE Transactions on Automatic Control, 65(8):3576–3583, 2020.
- Model predictive control: theory, computation, and design, volume 2. Nob Hill Publishing Madison, WI, 2017.
- Working together: A review on safe human-robot collaboration in industrial environments. IEEE Access, 5:26754–26773, 2017.
- Suboptimal model predictive control (feasibility implies stability). IEEE Transactions on Automatic Control, 44(3):648–654, 1999.
- Augmenting MPC schemes with active learning: Intuitive tuning and guaranteed performance. IEEE Control Systems Letters, 4(3):713–718, 2020.
- Linear model predictive safety certification for learning-based control. In 2018 IEEE Conference on Decision and Control (CDC), pages 7130–7135, 2018.