Safety for control systems is often posed as an invariance constraint; the system is said to be safe if state trajectories avoid some unsafe region of the statespace for all time. An assured controller is one that enforces safety online by filtering a desired control input at runtime, and control barrier functions (CBFs) provide an assured controller that renders a safe subset of the state-space forward invariant. Recent extensions propose CBF-based assured controllers that allow the system to leave a known safe set so long as a given backup control strategy eventually returns to the safe set, however, these methods have yet to be extended to consider systems subjected to unknown disturbance inputs.
In this work, we present a problem formulation for CBF-based runtime assurance for systems with disturbances, and controllers which solve this problem must, in some way, incorporate the online computation of reachable sets. In general, computing reachable sets in the presence of disturbances is computationally costly and cannot be directly incorporated in a CBF framework. To that end, we present a particular solution to the problem, whereby reachable sets are approximated via the mixed-monotonicity property. Efficient algorithms exist for overapproximating reachable sets for mixed-monotone systems with hyperrectangles, and we show that such approximations are suitable for incorporating into a CBF-based runtime assurance framework.
This paper proposes a method to synthesise controllers for cyber-physical systems such that the controlled systems satisfy specifications given as linear temporal logic formulas. The focus is on systems with disturbance, where future states cannot be predicted exactly due to uncertainty in the environment. The approach used to solve this problem is to first construct a finite-state abstraction of the original system and then synthesise a controller for the abstract system. For this approach, the robust stutter bisimulation relation is introduced, which preserves the existence of controllers fo…
RTD-RAX: Fast, Safe Trajectory Planning for Systems under Unknown Disturbances
Georgia Institute of Technology（佐治亚理工学院）；School of Electrical and Computer Engineering（电子与计算机工程学院）；School of Mechanical Engineering（机械工程学院）；School of Civil and Environmental Engineering（土木与环境工程学院）
Virginia Tech（弗吉尼亚理工大学）；University of Southern California（南加州大学）
Cyber-physical systems are often safety-critical in that violations of safety properties may lead to catastrophes. We propose a method to enforce the safety of systems with real-valued signals by synthesizing a runtime enforcer called the shield. Whenever the system violates a property, the shield, composed with the system, makes correction instantaneously to ensure that no erroneous output is generated by the combined system. While techniques for synthesizing Boolean shields are well understood, they do not handle real-valued signals ubiquitous in cyber-physical systems, meaning corrections m…
This paper introduces an $\mathcal{L}_1$ adaptive control augmentation for geometric tracking control of quadrotors. In the proposed design, the $\mathcal{L}_1$ augmentation handles nonlinear (time- and state-dependent) uncertainties in the quadrotor dynamics without assuming or enforcing parametric structures, while the baseline geometric controller achieves stabilization of the known nonlinear model of the system dynamics. The $\mathcal{L}_1$ augmentation applies to both the rotational and the translational dynamics. Experimental results demonstrate that the augmented geometric controller sh…
Source Side Mitigation of AI Datacenter Power Fluctuations with a Hybrid Energy Storage System and Residual Differentiable Predictive Control
James Watt School of Engineering, University of Glasgow（格拉斯哥大学詹姆斯·瓦特工程学院）；College of Information and Electrical Engineering, China Agricultural University（中国农业大学信息与电气工程学院）
Model-Free Based Computations of Recursive Control Barrier Function: Ultra-Local Model Approach
Nantes Université- École Centrale Nantes-LS2N, UMR 6004 CNRS（南特大学-南特中央理工学院-LS2N，UMR 6004 CNRS）；University of California, Merced - Dep. of Mechanical Engineering（加州大学默塞德分校-机械工程系）；QUARTZ EA 7393, ENSEA（QUARTZ EA 7393，恩赛纳）
