Simulation of Two-Rate Adaptive Hybrid Control with Neural and Neuro-Fuzzy Networks for Stochastic Model of an Experimental Aircraft

摘要

This paper presents a research methodology for describing a two-rate stochastic control system as State-Space (SS) type decomposed models of Multi-Input/Multi-Output (MIMO) stochastic control subsystems with the Neural Networks (NNs), and with the Neuro-Fuzzy Networks (NFNs) of different structure. The block diagrams both the original system with Linear-Quadratic-Gaussian (LQG) regulator and decomposed subsystems with two-rate adaptive hybrid control with NNs and NFNs for stochastic model of a tracking system for an experimental aircraft were designed. The simulation results with use of software package Simulink demonstrate that this technique would work for real-time MIMO stochastic systems.