Computationally efficient nonlinear predictive control based on state-space neural models
M Ławryńczuk - Parallel Processing and Applied Mathematics: 8th …, 2010 - Springer
This paper describes a computationally efficient nonlinear Model Predictive Control (MPC)
algorithm in which a state-space neural model of the process is used on-line. The model …
algorithm in which a state-space neural model of the process is used on-line. The model …
Contribution à la synthèse de contrôleurs neuronaux robustes par imitation
J Pinguet - 2023 - theses.fr
Résumé Cette thèse s' intéresse à l'élaboration de systèmes de contrôle par imitation de
comportements ou de décisions répondant à des exigences complexes. L'objectif est de …
comportements ou de décisions répondant à des exigences complexes. L'objectif est de …
Machine learning with nonlinear state space models
M Schüssler - at-Automatisierungstechnik, 2022 - degruyter.com
In this dissertation, a novel class of model structures and associated training algorithms for
building data-driven nonlinear state space models is developed. The new identification …
building data-driven nonlinear state space models is developed. The new identification …
Enhancing neural network prediction against unknown disturbances with neural network disturbance observer
M Pouilly-Cathelain, P Feyel… - … on Informatics in …, 2019 - centralesupelec.hal.science
Neural network prediction is a very challenging subject in the presence of disturbances. The
difficulty comes from the lack of knowledge about perturbation. Most papers related to …
difficulty comes from the lack of knowledge about perturbation. Most papers related to …
[图书][B] Condition monitoring and fault diagnosis by principal component analysis and nonlinear PCA
J Shan - 2006 - search.proquest.com
Early detection and diagnosis of process faults while the plant is still operating in a
controllable region can help avoid abnormal event progression and reduce productivity loss …
controllable region can help avoid abnormal event progression and reduce productivity loss …
Robust multi-model fault detection and isolation with a state-space neural network
A Czajkowski, M Luzar… - 2016 24th Mediterranean …, 2016 - ieeexplore.ieee.org
This paper presents an design of a Robust Fault Detection and Isolation (FDI) diagnostic
system by the means of state-space neural network. First, an solution utilizing multimodel …
system by the means of state-space neural network. First, an solution utilizing multimodel …
Design of sensor and actuator multi model fault detection and isolation system using state space neural networks
A Czajkowski - Journal of Physics: Conference Series, 2015 - iopscience.iop.org
This paper deals with the application of state space neural network model to design a Fault
Detection and Isolation diagnostic system. The work describes approach based on …
Detection and Isolation diagnostic system. The work describes approach based on …
Red neuronal estructurada en el espacio de estados como modelo de caja gris
J Zamarreño, A Merino - XL Jornadas de Automática, 2019 - ruc.udc.es
La Red Neuronal en el Espacio de Estados (RNEE) ha demostrado muy buenas
propiedades en el modelado de sistemas dinámicos. En este artículo, proponemos una …
propiedades en el modelado de sistemas dinámicos. En este artículo, proponemos una …
基于神经状态空间的非线性系统建模研究
王永骥， 吴庆， 王宏 - 系统仿真学报, 2001 - cqvip.com
提出了一种基于神经状态空间的非线性系统建模方法. 神经状态空间(NNSP)
具有系统的拟线性特性, 许多线性系统控制器设计方法均可以扩展到NNSP 模型 …
具有系统的拟线性特性, 许多线性系统控制器设计方法均可以扩展到NNSP 模型 …
Fault accommodation of the two rotor aero-dynamical system using the state space neural networks based model predictive control
A Czajkowski, K Patan - … on Methods and Models in Automation …, 2014 - ieeexplore.ieee.org
This paper deals with the application of state space neural network model to design a model
predictive control for a laboratory stand of the Two Rotor Aero-dynamical system. The work …
predictive control for a laboratory stand of the Two Rotor Aero-dynamical system. The work …