Search Results for author:
Found 9 papers, 2 papers with code
Neural Differentiable Integral Control Barrier Functions for Unknown Nonlinear Systems with Input Constraints
In this paper, we propose a deep learning based control synthesis framework for fast and online computation of controllers that guarantees the safety of general nonlinear control systems with unknown dynamics in the presence of input constraints.
Disturbance Observer-based Robust Integral Control Barrier Functions for Nonlinear Systems with High Relative Degree
Towards this aim, we first construct a governing augmented state space model consisting of the equations of motion of the original system, the integral control law and the nonlinear disturbance observer.
Semi-global Exponential Stability for Dual Quaternion Based Rigid-Body Tracking Control
Semi-Global Exponential Stability (SGES) is proved for the combined attitude and position rigid body motion tracking problem, which was previously only known to be asymptotically stable.
Neural Koopman Control Barrier Functions for Safety-Critical Control of Unknown Nonlinear Systems
We prove that the learned CBF for the latter bilinear system is also a valid CBF for the unknown nonlinear system by characterizing the $\ell^2$-norm error bound between these two systems.
Neural Koopman Lyapunov Control
In this paper, we propose a framework to construct these stabilizable bilinear models and identify its associated observables from data by simultaneously learning a bilinear Koopman embedding for the underlying unknown control affine nonlinear system as well as a Control Lyapunov Function (CLF) for the Koopman based bilinear model using a learner and falsifier.
Koopman Operator Based Modeling and Control of Rigid Body Motion Represented by Dual Quaternions
In this paper, we systematically derive a finite set of Koopman based observables to construct a lifted linear state space model that describes the rigid body dynamics based on the dual quaternion representation.
Optimal Sensor Gain Control for Minimum-Information Estimation of Continuous-Time Gauss-Markov Processes
We consider the scenario in which a continuous-time Gauss-Markov process is estimated by the Kalman-Bucy filter over a Gaussian channel (sensor) with a variable sensor gain.
Minimum-fuel Spacecraft Rendezvous based on Sparsity Promoting Optimization
In this paper, we consider the classical spacecraft rendezvous problem in which the so-called active spacecraft has to approach the target spacecraft which is moving in an elliptical orbit around a planet by using the minimum possible amount of fuel.
Koopman Operator Based Modeling for Quadrotor Control on $SE(3)$
In this paper, we propose a Koopman operator based approach to describe the nonlinear dynamics of a quadrotor on SE(3) in terms of an infinite-dimensional linear system which evolves in the space of observable functions (lifted space) and which is more appropriate for control design purposes.
