Zobrazeno 1 - 10
of 551
pro vyhledávání: '"Cannon, Mark"'
We present a novel targeted exploration strategy for linear time-invariant systems without stochastic assumptions on the noise, i.e., without requiring independence or zero mean, allowing for deterministic model misspecifications. This work utilizes
Externí odkaz:
http://arxiv.org/abs/2312.05947
This paper investigates robust tube-based Model Predictive Control (MPC) of a tiltwing Vertical Take-Off and Landing (VTOL) aircraft subject to wind disturbances and model uncertainty. Our approach is based on a Difference of Convex (DC) function dec
Externí odkaz:
http://arxiv.org/abs/2308.03557
This paper is concerned with model predictive control (MPC) of discrete-time linear systems subject to bounded additive disturbance and mixed constraints on the state and input, whereas the true disturbance set is unknown. Unlike most existing work o
Externí odkaz:
http://arxiv.org/abs/2304.05105
Autor:
Lishkova, Yana, Cannon, Mark
A novel robust nonlinear model predictive control strategy is proposed for systems with nonlinear dynamics and convex state and control constraints. Using a sequential convex approximation approach and a difference of convex functions representation,
Externí odkaz:
http://arxiv.org/abs/2302.07744
We propose a method to generate robust and optimal trajectories for the transition of a tiltwing Vertical Take-Off and Landing (VTOL) aircraft leveraging concepts from convex optimisation, tube-based nonlinear Model Predictive Control (MPC) and Diffe
Externí odkaz:
http://arxiv.org/abs/2302.04361
Autor:
Lu, Xiaonan, Cannon, Mark
We propose a robust adaptive Model Predictive Control (MPC) strategy with online set-based estimation for constrained linear systems with unknown parameters and bounded disturbances. A sample-based test applied to predicted trajectories is used to en
Externí odkaz:
http://arxiv.org/abs/2211.12478
Autor:
Lu, Xiaonan, Cannon, Mark
For constrained linear systems with bounded disturbances and parametric uncertainty, we propose a robust adaptive model predictive control strategy with online parameter estimation. Constraints enforcing persistently exciting closed loop control acti
Externí odkaz:
http://arxiv.org/abs/2211.09275
This paper describes the design of a safeguarding scheme for Anderson acceleration to improve its practical performance and stability when used for first-order optimisation methods. We show how the combination of a non-expansiveness condition, condit
Externí odkaz:
http://arxiv.org/abs/2208.02847