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Found 8 papers, 0 papers with code
Robust optimization for adversarial learning with finite sample complexity guarantees
Decision making and learning in the presence of uncertainty has attracted significant attention in view of the increasing need to achieve robust and reliable operations.
Learning Robust Policies for Uncertain Parametric Markov Decision Processes
Synthesising verifiably correct controllers for dynamical systems is crucial for safety-critical problems.
Distributed Safe Control Design and Safety Verification for Multi-Agent Systems
Both the scenario sampling and safety verification procedures are fully distributed.
Multi-objective low-thrust spacecraft trajectory design using reachability analysis
One of the fundamental problems in spacecraft trajectory design is finding the optimal transfer trajectory that minimizes the propellant consumption and transfer time simultaneously.
Tracking-based distributed equilibrium seeking for aggregative games
We propose fully-distributed algorithms for Nash equilibrium seeking in aggregative games over networks.
Safety-Aware Optimal Control for Motion Planning with Low Computing Complexity
Simulations demonstrates that BRSCA has a higher probability of finding feasible solutions, reduces the computation time by about 17. 4% and the energy cost by about four times compared to other methods in the literature.
Verification of safety critical control policies using kernel methods
Hamilton-Jacobi reachability methods for safety-critical control have been well studied, but the safety guarantees derived rely on the accuracy of the numerical computation.
Probabilistic stabilizability certificates for a class of black-box linear systems
We provide out-of-sample certificates on the controlled invariance property of a given set with respect to a class of black-box linear systems.
Optimization and Control Systems and Control Systems and Control
