scholarly journals Stochastic Model Predictive Control for Water Transport Networks with Demand Forecast Uncertainty

2017 ◽  
pp. 269-290
Author(s):  
Juan Manuel Grosso ◽  
Carlos Ocampo-Martínez ◽  
Vicenç Puig
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Water Transport ◽  
Predictive Control ◽  
Demand Forecast ◽  
Transport Networks ◽  
Forecast Uncertainty ◽  
Stochastic Model Predictive Control

scholarly journals Reference tracking stochastic model predictive control over unreliable channels and bounded control actions

Automatica ◽  
2021 ◽  
Vol 127 ◽  
pp. 109512
Author(s):  
Prabhat K. Mishra ◽  
Sanket S. Diwale ◽  
Colin N. Jones ◽  
Debasish Chatterjee
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Bounded Control ◽  
Reference Tracking ◽  
Control Actions ◽  
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.

Stochastic model predictive control without terminal constraints

2017 ◽  
Vol 29 (15) ◽  
pp. 4987-5001 ◽  
Author(s):  
Matthias Lorenzen ◽  
Matthias A. Müller ◽  
Frank Allgöwer
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Terminal Constraints ◽  
Stochastic Model Predictive Control

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
Sign in / Sign up

Export Citation Format

Share Document