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Found 5 papers, 0 papers with code
Observer-Based Environment Robust Control Barrier Functions for Safety-critical Control with Dynamic Obstacles
This paper proposes a safety-critical controller for dynamic and uncertain environments, leveraging a robust environment control barrier function (ECBF) to enhance the robustness against the measurement and prediction uncertainties associated with moving obstacles.
K-SMPC: Koopman Operator-Based Stochastic Model Predictive Control for Enhanced Lateral Control of Autonomous Vehicles
Thus, we use the Koopman operator to represent the nonlinear dynamics of a vehicle in dynamic lane-keeping situations.
Uncertainty Quantification of Autoencoder-based Koopman Operator
We approximate the Koopman operator in a finite-dimensional space with the autoencoder, while the approximated Koopman has an approximation uncertainty.
RNN Controller for Lane-Keeping Systems with Robustness and Safety Verification
This paper proposes a Recurrent Neural Network (RNN) controller for lane-keeping systems, effectively handling model uncertainties and disturbances.
Robust Control for Lane Keeping System Using Linear Parameter Varying Approach with Scheduling Variables Reduction
In this paper, to reduce the computational complexity, Principal Component Analysis (PCA)-based parameter reduction is performed to obtain a reduced model with a tighter convex set.
