7 papers
Non-asymptotic Bounds of Learning-based Linear MPC With Input Constraints and Unbounded Stochastic Noise
Changyi Lei, Seth Siriya, Dragan Nešić +1
This paper studies learning-based model predictive control (MPC) for stabilizing unknown discrete-time linear systems with hard input constraints and additive unbounded sub-Gaussia…
Learning-based Homothetic Tube MPC with Non-Asymptotic Guarantees
Changyi Lei, Seth Siriya, Dragan Nešić +1
This paper studies learning-based MPC for constrained stabilization of discrete-time linear systems with unknown system parameters and additive bounded disturbances. We develop a t…
A PAC-Bayes Approach for Controlling Unknown Linear Discrete-time Systems
Yujia Luo, Ye Pu, Jonathan H. Manton +1
This paper presents a PAC-Bayes framework for learning controllers for unknown stochastic linear discrete-time systems, where the system parameters are drawn from a fixed but unkno…
A Framework for Adaptive Stabilisation of Nonlinear Stochastic Systems
Seth Siriya, Jingge Zhu, Dragan Nešić +1
We consider the adaptive control problem for discrete-time, nonlinear stochastic systems with linearly parameterised uncertainty. Assuming access to a parameterised family of contr…
Towards Fast and Safety-Guaranteed Trajectory Planning and Tracking for Time-Varying Systems
Seth Siriya, Mo Chen, Ye Pu
When deploying autonomous systems in unknown and changing environments, it is critical that their motion planning and control algorithms are computationally efficient and can be re…
Non-Asymptotic Bounds for Closed-Loop Identification of Sub-Exponentially Growing Nonlinear Stochastic Systems
Seth Siriya, Jingge Zhu, Dragan Nešić +1
We investigate the problem of least squares parameter estimation from single-trajectory data for discrete-time, unstable, closed-loop nonlinear stochastic systems. Specifically, we…
Task-Oriented Koopman-Based Control with Contrastive Encoder
Xubo Lyu, Hanyang Hu, Seth Siriya +2
We present task-oriented Koopman-based control that utilizes end-to-end reinforcement learning and contrastive encoder to simultaneously learn the Koopman latent embedding, operato…