Search Results for author:
Found 8 papers, 2 papers with code
Deep Learning Model Predictive Control for Deep Brain Stimulation in Parkinson's Disease
We present a nonlinear data-driven Model Predictive Control (MPC) algorithm for deep brain stimulation (DBS) for the treatment of Parkinson's disease (PD).
Towards targeted exploration for non-stochastic disturbances
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.
Data-driven robust MPC of tiltwing VTOL aircraft
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.
Stochastic output feedback MPC with intermittent observations
We analyse robustness of the proposed control law with respect to possible uncertainties in the arrival probability of sensor data and we bound the impact of these uncertainties on constraint satisfaction and the discounted cost.
Stochastic MPC with Dynamic Feedback Gain Selection and Discounted Probabilistic Constraints
With dynamic feedback gain selection, the closed loop cost is reduced and conservativeness of Chebyshev's inequality is mitigated.
Infinite-Horizon Differentiable Model Predictive Control
This paper proposes a differentiable linear quadratic Model Predictive Control (MPC) framework for safe imitation learning.
Parallel ADMM for robust quadratic optimal resource allocation problems
An alternating direction method of multipliers (ADMM) solver is described for optimal resource allocation problems with separable convex quadratic costs and constraints and linear coupling constraints.
Optimization and Control 90C25, 93E20, 65Y05, 65Y20
COSMO: A conic operator splitting method for convex conic problems
This paper describes the Conic Operator Splitting Method (COSMO) solver, an operator splitting algorithm for convex optimisation problems with quadratic objective function and conic constraints.
Optimization and Control
