Stochastic Model Predictive Control with adaptive constraint tightening for non-conservative chance constraints satisfaction

Automatica ◽  
2018 ◽  
Vol 96 ◽  
pp. 32-39 ◽  
Author(s):  
Diego Muñoz-Carpintero ◽  
Guoqiang Hu ◽  
Costas J. Spanos
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Chance Constraints ◽  
Stochastic Model Predictive Control ◽  
Constraints Satisfaction

scholarly journals Stochastic model predictive control with joint chance constraints

2017 ◽  
Vol 93 (1) ◽  
pp. 126-139 ◽  
Author(s):  
Joel A. Paulson ◽  
Edward A. Buehler ◽  
Richard D. Braatz ◽  
Ali Mesbah
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Chance Constraints ◽  
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.

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