Anticipating Meals with Behavioral Profiles: Towards Stochastic Model Predictive Control of T1DM* *This work was sponsored in part by (1) the Juvenile Diabetes Research Foundation (JDRF) Artificial Pancreas Project and (2) the National Library of Medicine (Award Number T15LM009462). This content is solely the responsibility of the authors and does not necessarily represent the official views of the JDRF, the National Library of Medicine, or the National Institutes of Health.

2009 ◽  
Vol 42 (12) ◽  
pp. 37-42
Author(s):  
S.D. Patek ◽  
C. Hughes ◽  
M. Breton ◽  
B.P. Kovatchev
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Artificial Pancreas ◽  
Juvenile Diabetes ◽  
National Institutes Of Health ◽  
Diabetes Research ◽  
National Library ◽  
Behavioral Profiles ◽  
Stochastic Model Predictive Control

STOCHASTIC MODEL PREDICTIVE CONTROL FOR SPACECRAFT RENDEZVOUS AND DOCKING VIA A DISTRIBUTIONALLY ROBUST OPTIMIZATION APPROACH

2021 ◽  
pp. 1-19
Author(s):  
ZUOXUN LI ◽  
KAI ZHANG
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Robust Optimization ◽  
Predictive Control ◽  
Attitude Control ◽  
Optimization Approach ◽  
Distributionally Robust Optimization ◽  
Distributionally Robust ◽  
Stochastic Model Predictive Control ◽  
Rendezvous And Docking

Abstract A stochastic model predictive control (SMPC) algorithm is developed to solve the problem of three-dimensional spacecraft rendezvous and docking with unbounded disturbance. In particular, we only assume that the mean and variance information of the disturbance is available. In other words, the probability density function of the disturbance distribution is not fully known. Obstacle avoidance is considered during the rendezvous phase. Line-of-sight cone, attitude control bandwidth, and thrust direction constraints are considered during the docking phase. A distributionally robust optimization based algorithm is then proposed by reformulating the SMPC problem into a convex optimization problem. Numerical examples show that the proposed method improves the existing model predictive control based strategy and the robust model predictive control based strategy in the presence of disturbance.

A Stochastic Model Predictive Control Framework for Stationary Battery Systems

2018 ◽  
Vol 33 (4) ◽  
pp. 4397-4406 ◽  
Author(s):  
Ranjeet Kumar ◽  
Michael J. Wenzel ◽  
Matthew J. Ellis ◽  
Mohammad N. ElBsat ◽  
Kirk H. Drees ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Control Framework ◽  
Battery Systems ◽  
Stochastic Model Predictive Control
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