Fault tolerant control using Gaussian processes and model predictive control

DOI10.1515/amcs-2015-0010zbMath1322.93044OpenAlexW2180534877MaRDI QIDQ747454

Xiaoke Yang, Jan M. Maciejowski

Publication date: 16 October 2015

Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/amcs-2015-0010

zbMATH Keywords

Gaussian processmodel predictive controlaircraft controlfault-tolerant controlprobabilistic modelling

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) Application models in control theory (93C95)

Related Items (8)

Stochastic tracking control of multivariable nonlinear systems subject to external disturbances ⋮ Online learning‐based model predictive control with Gaussian process models and stability guarantees ⋮ Offset-free state-space nonlinear predictive control for Wiener systems ⋮ Assessment of the GPC control quality using non-Gaussian statistical measures ⋮ Robust MPC for actuator-fault tolerance using set-based passive fault detection and active fault isolation ⋮ Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm ⋮ Actuator failure compensation for two linked 2WD mobile robots based on multiple-model control ⋮ High-probability stable Gaussian process-supported model predictive control for Lur'e systems

Uses Software

• Ipopt
• PILCO

Cites Work

• On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming
• Introduction to stochastic control theory
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