Constructing a Generalized Lyapunov Barrier Function for Safe Stabilization of Nonlinear Control Systems
This paper introduces the concept of a generalized (nonsmooth) Lyapunov barrier function (GenLBF) to unify control Lyapunov function (CLF) and control barrier function (CBF) for certifying KL-stability and safety of nonlinear control systems. The authors propose a systematic approach for constructing a suitable GenLBF and an efficient method for evaluating its generalized derivative. The GenLBF-based control design ensures safe stabilization of both autonomous and non-autonomous systems.
Unified Lyapunov Conditions for Predefined-time and Finite-time Stability of Nonlinear Systems
This paper presents unified sufficient Lyapunov conditions to guarantee the predefined-time and finite-time stability of autonomous nonlinear systems. The proposed Lyapunov theorem consolidates and generalizes existing results on predefined-time and finite-time stability.
Stochastic Safety with Freedman’s Inequality in Discrete-Time Control Barrier Functions
Utilizing Freedman’s inequality in discrete-time control barrier functions provides stronger safety guarantees for stochastic systems.
Continuous-time q-learning for mean-field control problems: Integrated q-functions and learning algorithms
Continuous-time q-learning introduces integrated q-functions for mean-field control problems, enabling efficient learning algorithms.
Dimensionless Policies based on the Buckingham π Theorem: Generalizing Numerical Results
Die Verwendung des Buckingham π-Theorems ermöglicht die Verallgemeinerung von numerischen Ergebnissen für Bewegungssteuerungsprobleme.
Reachable Sets' Convex Hulls Analysis
Characterizing the convex hulls of reachable sets simplifies estimation algorithms efficiently.
Harmonic Control Lyapunov Barrier Functions for Constrained Optimal Control with Reach-Avoid Specifications
Harmonic Control Lyapunov Barrier Functions provide stability and safety guarantees for reach-avoid problems in control systems.
Robust Model Based Reinforcement Learning Using L1 Adaptive Control at ICLR 2024
Introducing L1-MBRL for robust reinforcement learning with model-based algorithms.
DREM with Annihilators for Unbiased Parameter Estimation
Modification of DREM procedure eliminates bias in parameter estimation.
Dissipative Gradient Descent Ascent Method: A Control Theory Inspired Algorithm for Min-max Optimization
DGDA method introduces a dissipation term to stabilize oscillatory behavior in GDA, achieving superior convergence rates.
