DocumentCode :
1561448
Title :
Simulation of two-rate adaptive hybrid control with neural and neuro-fuzzy networks for stochastic model of missile autopilot
Author :
Astrov, Igor ; Pedai, Andms ; Rustern, E.
Author_Institution :
Dept. of Comput. Control, Tallinn Univ. of Technol., Estonia
Volume :
3
fYear :
2004
Firstpage :
2603
Abstract :
This paper describes a two-rate stochastic control system as state-space (SS) type decomposed and discretized models of multi-input/multi-output (MIMO) stochastic subsystems with the "fast" and "slow" control neural networks (NNs) and with the "fast" and "slow" neuro-fuzzy networks (NFNs). The block diagrams both the original system with linear-quadratic-Gaussian (LQG) regular and decomposed subsystems with two-rate NNs and NFNs hybrid adaptive control were designed. An illustrative example - two-rate NN and NFN hybrid control of decomposed stochastic model of a rigid guided missile over different operating conditions was carried out using the proposed two-rate SS decomposition technique. This example demonstrates that this research technique results in simplified low-order autonomous control subsystems with various discretization periods and with various speeds of actuation, and shows the quality of the proposed technique. The obtained results show that the control tasks for the autonomous subsystems can be solved more qualitatively than for the original system. This simulation and animation results with use of software package Simulink demonstrate that this research technique would work for real-time stochastic systems.
Keywords :
MIMO systems; adaptive control; digital simulation; discrete time systems; fuzzy neural nets; linear quadratic Gaussian control; missile control; multivariable control systems; neurocontrollers; real-time systems; sampled data systems; software packages; state-space methods; stochastic systems; MIMO system; Simulink; autonomous control subsystem; linear quadratic Gaussian decomposed subsystem; linear quadratic Gaussian regular subsystem; missile autopilot; multipleinput multipleoutput system; neuro fuzzy networks; rigid guided missile; software package; two rate adaptive hybrid control; two rate stochastic control system; Adaptive control; Control system synthesis; Control systems; Fuzzy neural networks; MIMO; Missiles; Neural networks; Programmable control; Stochastic processes; Stochastic systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
Type :
conf
DOI :
10.1109/WCICA.2004.1342067
Filename :
1342067
Link To Document :
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