A Simulation Environment for Testing and Research of Neurally Augmented Fault Tolerant Control Laws Based on Non-Linear Dynamic Inversion

2004 ◽  
Author(s):  
Mario Perhinschi ◽  
Marcello Napolitano ◽  
Giampiero Campa ◽  
Mario Fravolini
Keyword(s):  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Dynamic Inversion ◽  
Simulation Environment ◽  
Control Laws ◽  
Linear Dynamic ◽  
Non Linear

A Simulation Environment for Self-Propelled Gun Failure Prediction Based on Probabilistic Neural Network

2012 ◽  
Vol 466-467 ◽  
pp. 1424-1428
Author(s):  
Guang Hong ◽  
Shuai Zhang
Keyword(s):  
Neural Network ◽  
Fault Tolerant ◽  
Probabilistic Neural Network ◽  
Failure Prediction ◽  
Fault Tolerant Control ◽  
Simulation Environment ◽  
Control Laws ◽  
Input Module ◽  
Output Module ◽  
Engine Failure

This paper presents the development of a simulation environment in Matlab/Simulink for the analysis of the Sub-System of a kind of self-propelled gun and the design of fault tolerant control laws for this configuration. The environment includes the input module, output module and Simulation Nucleus and modeling of several types of engine failure. The simulation environment capable of implementing failure prediction has been implemented successfully as groundwork for analysis of the engine subsystem of self-propelled gun. Preliminary simulation results show the simulation environment is efficient for the Probabilistic neural network. Both abnormal oil pressure and rotate speed failures have been simulated. The simulation environment provides the necessary tools for the development and testing of advanced fault tolerant control laws.

scholarly journals DNN identification and fault-tolerant control for non-linear systems with unknown faults

2019 ◽  
Vol 2019 (22) ◽  
pp. 8395-8399 ◽  
Author(s):  
Xiaoli Zhang ◽  
Xiang Gu ◽  
Hong Shen ◽  
Yang Yi
Keyword(s):  
Linear Systems ◽  
Fault Tolerant ◽  
Fault Tolerant Control ◽  
Non Linear ◽  
Non Linear Systems
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