The field of control systems is moving towards the development of more robust and safety-critical systems. Recent research has focused on the use of model predictive control, Koopman operators, and control barrier functions to ensure safety and stability in complex systems. These approaches have been applied to a variety of domains, including autonomous vehicles, robotics, and biomolecular systems. Notable papers in this area include 'Safety Assessment in Reinforcement Learning via Model Predictive Control', which proposes a method for preventing safety issues in reinforcement learning, and 'Robust Multi-Agent Safety via Tube-Based Tightened Exponential Barrier Functions', which presents a framework for synthesizing provably safe controllers for nonlinear multi-agent systems. Overall, the field is seeing a shift towards more data-driven and adaptive approaches to control system design, with a focus on ensuring safety and stability in the presence of uncertainty and disturbance.
Advances in Safety-Critical Control Systems
Sources
Safety Assessment in Reinforcement Learning via Model Predictive Control
Data-driven Koopman MPC using Mixed Stochastic-Deterministic Tubes
Predictive control barrier functions for piecewise affine systems with non-smooth constraints
Learning Neural Control Barrier Functions from Expert Demonstrations using Inverse Constraint Learning
Rate-cost tradeoffs in continuous-time control with a biomolecular application
An Introductory Guide to Koopman Learning
Vector-Valued Native Space Embedding for Adaptive State Observation
Functional Uncertainty Classes, Nonparametric Adaptive Contro Functional Uncertainty Classes for Nonparametric Adaptive Control: the Curse of Dimensionality
Robust Multi-Agent Safety via Tube-Based Tightened Exponential Barrier Functions
Ellipsoidal Set-Theoretic Design of Robust Safety Filters for Constrained Linear Systems
Numerical Spectrum Linking: Identification of Governing PDE via Koopman-Chebyshev Approximation
T-ESKF: Transformed Error-State Kalman Filter for Consistent Visual-Inertial Navigation
An Error-Based Safety Buffer for Safe Adaptive Control (Extended Version)
A Hamilton-Jacobi Reachability Framework with Soft Constraints for Safety-Critical Systems
Modulation Schemes for Functionalized Vesicle-based MC Transmitters
Risk-Aware Safety Filters with Poisson Safety Functions and Laplace Guidance Fields
Safety Margins of Inverse Optimal ISSf Controllers