A Moving-Mass Control System for Spinning Vehicle Based on Neural Networks and Genetic Algorithm

2005 ◽  
pp. 172-178
Author(s):  
Song-yan Wang ◽  
Ming Yang ◽  
Zi-cai Wang
Keyword(s):  
Genetic Algorithm ◽  
Neural Networks ◽  
Control System ◽  
Moving Mass ◽  
Moving Mass Control

RBF Neural Network-Based Terminal Sliding Mode Control for Reentry Warhead

2011 ◽  
Vol 63-64 ◽  
pp. 381-384
Author(s):  
Hong Chao Zhao ◽  
Jie Chen ◽  
Hua Zhang Liu
Keyword(s):  
Neural Network ◽  
Control System ◽  
Finite Time ◽  
Sliding Mode ◽  
Rbf Neural Network ◽  
Research Result ◽  
Sliding Mode Controller ◽  
Moving Mass ◽  
Terminal Sliding Mode ◽  
Moving Mass Control

The existing moving mass control system of a nonspinning reentry warhead could not drive the system error to reach zero in finite time. In order to settle the finite time reach issue, an RBF neural network-based terminal sliding mode controller was presented to design the moving mass control system. It used a terminal sliding mode to ensure that the error reaches zero in finite time. The disturbance and coupled terms of the warhead were treated as uncertainties. An RBF neural network was used to estimate the uncertainties. A nonspinning warhead was taken in the simulation to test the performance of the presented controller. The simulation results show the presented controller has faster tracking speed and higher tracking precision than the former research result.

Modeling and Variable Structure Control of Autonomous Underwater Vehicles with Moving Mass

2011 ◽  
Vol 130-134 ◽  
pp. 1963-1967 ◽  
Author(s):  
E Zhao ◽  
Bao Wei Song
Keyword(s):  
Control System ◽  
Control Method ◽  
Sliding Mode ◽  
Autonomous Underwater Vehicles ◽  
Tracking Error ◽  
Variable Structure Control ◽  
Variable Structure ◽  
Moving Mass ◽  
Structure Control ◽  
Moving Mass Control

In order to solve the problem of general fins and rudders being lower at low moving speed, the moving mass technical is applied onto AUV, thus to radically solve the weakness of control method with fin and rudder. The space dynamics model of moving mass control is created for AUV. And based on this, the moving mass control system is designed with the sliding mode variable structure control method so as to ensure system tracking error zero convergence. By controlling the moving mass movement with moving mass control system, the attitude of AVU is previously controlled. And simulation result proves that moving mass control system will control the AUV attitude angle precisely and rapidly.

Modeling of Self-Induced Vibrations that Occur During the Machining Process of Casting Patterns with the Use of The Fuzzy-Neural Networks Method

2013 ◽  
Vol 58 (3) ◽  
pp. 871-875
Author(s):  
A. Herberg
Keyword(s):  
Neural Networks ◽  
Control System ◽  
Network Structure ◽  
Fuzzy Systems ◽  
Fuzzy Neural Networks ◽  
Cnc Machining ◽  
Machining Process ◽  
Modeling Process ◽  
Fuzzy Neural ◽  
Takagi Sugeno

Abstract This article outlines a methodology of modeling self-induced vibrations that occur in the course of machining of metal objects, i.e. when shaping casting patterns on CNC machining centers. The modeling process presented here is based on an algorithm that makes use of local model fuzzy-neural networks. The algorithm falls back on the advantages of fuzzy systems with Takagi-Sugeno-Kanga (TSK) consequences and neural networks with auxiliary modules that help optimize and shorten the time needed to identify the best possible network structure. The modeling of self-induced vibrations allows analyzing how the vibrations come into being. This in turn makes it possible to develop effective ways of eliminating these vibrations and, ultimately, designing a practical control system that would dispose of the vibrations altogether.

Sign in / Sign up

Export Citation Format

Share Document