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eess.SY2020
A Data-Driven Automatic Tuning Method for MPC under Uncertainty using Constrained Bayesian Optimization
Farshud Sorourifar, Georgios Makrygirgos, Ali Mesbah +1
The closed-loop performance of model predictive controllers (MPCs) is sensitive to the choice of prediction models, controller formulation, and tuning parameters. However, predicti…
eess.SY2020
Data-Driven Scenario Optimization for Automated Controller Tuning with Probabilistic Performance Guarantees
Joel A. Paulson, Ali Mesbah
Systematic design and verification of advanced control strategies for complex systems under uncertainty largely remains an open problem. Despite the promise of blackbox optimizatio…
eess.SY2020
PoCET: a Polynomial Chaos Expansion Toolbox for Matlab
Felix Petzke, Ali Mesbah, Stefan Streif
We introduce PoCET: a free and open-scource Polynomial Chaos Expansion Toolbox for Matlab, featuring the automatic generation of polynomial chaos expansion (PCE) for linear and non…