Research of Target Motion Model in Polar Coordinates Based on Dynamic Systems

2012 ◽  
Vol 496 ◽  
pp. 343-346
Author(s):  
Sheng Jie Zhao ◽  
Chuan Wang
Keyword(s):  
Monte Carlo ◽  
Dynamic Systems ◽  
Scientific Data ◽  
Target Motion ◽  
Polar Coordinates ◽  
Motion Model ◽  
Novel Target ◽  
Nonlinear Observation ◽  
Cv Model ◽  
Motion Mode

Abstract:Aiming at the nonlinear observation problem of target motion model in Cartesian coordinates, a novel target motion model in polar coordinates is proposed based on dynamic systems with analysis of scientific data materials. This paper has done about the target motion model in polar coordinates corresponding to CV model and CA respectively and simulated with Monte Carlo. The experimental results indicate that the target motion model is all agreed with targets motion in fact and can be used to describe the targets motion. Simulations show that state estimation of the KF based on the target motion mode with analysis of dynamic systems is efficient.

The solution problem of Dirihle for equation of Laplace in polar coordinates by method Monte Carlo

2018 ◽  
Vol 2 ◽  
pp. 114-122
Author(s):  
Yu.I. Nikolayenko ◽  
◽  
V.G. Ilvovsky ◽  
S.V. Moiseenko ◽  
◽  
...  
Keyword(s):  
Monte Carlo ◽  
Polar Coordinates ◽  
Solution Problem

scholarly journals Multi-Dimensional Harmonic Balance With Uncertainties Applied to Rotor Dynamics

2012 ◽  
Vol 134 (6) ◽  
Author(s):  
J. Didier ◽  
J.-J. Sinou ◽  
B. Faverjon
Keyword(s):  
Monte Carlo ◽  
Dynamic Systems ◽  
Harmonic Balance ◽  
Polynomial Chaos ◽  
Harmonic Balance Method ◽  
Numerical Approach ◽  
Rotor Dynamics ◽  
Geometrical Parameters ◽  
Chaos Expansion ◽  
Response Functions

This paper describes the coupling of a Multi-Dimensional Harmonic Balance Method (MHBM) with a Polynomial Chaos Expansion (PCE) to determine the dynamic response of quasi-periodic dynamic systems subjected to multiple excitations and uncertainties. The proposed method will be applied to a rotor system excited at its support. Uncertainties considered include both material and geometrical parameters as well as excitation sources. To demonstrate the effectiveness and validity of the proposed numerical approach, the results that include mean, variation of the response, envelopes of the Frequency Response Functions and orbits will be systematically compared to a classical Monte Carlo approach.

System Identification of Unmanned Planning Boat Rolling Motion Mode

2013 ◽  
Vol 823 ◽  
pp. 285-290
Author(s):  
Wang Lin Yang ◽  
Hai Tong Xu ◽  
Song Lin Yang ◽  
Sheng Zhang
Keyword(s):  
System Identification ◽  
Visual Basic ◽  
Roll Angle ◽  
Motion Model ◽  
Ship Model Test ◽  
Optimization Calculation ◽  
Object Of Study ◽  
Visual Basic 6.0 ◽  
Righting Moment ◽  
Motion Mode

In this paper, the author took an unmanned planning boat as the object of study and carried out a series of rolling decay ship model test by changing the draft. The author established nine kinds of mathematical model of rolling decay motion model system identification by using different damping and righting moment and established the optimization calculation of the objective function based on the principle of system identification. Then the author adapted the genetic algorithm of system identification program which is based on the Visual Basic 6.0 and got 15 kinds of identification programs. By doing research on the first three cycles of the series of rolling angular velocity curve and identifying respectively the resulting 15 kinds of identification programs, the author confirmed the feasibility of the adapted program. Comparing different drafts and the initial roll angle identification results, the author found a reasonable hydrostatic roll motion equation of the unmanned planning boat in the case of different drafts and the initial roll angle, and made a preliminary analysis.

scholarly journals A review of a motion model construction and simulation method for multi-level and multi-dimensional dynamic systems

2021 ◽  
Author(s):  
Guoxin Yang ◽  
Carl Yang
Keyword(s):  
Intellectual Property ◽  
Dynamic System ◽  
Dynamic Systems ◽  
Simulation Method ◽  
Model Construction ◽  
Motion Trajectory ◽  
Motion Model ◽  
Multi Level ◽  
Dynamic Subsystem ◽  
Dynamic Trajectory

On October 21, 2020, the invention “A multi-level and multi-dimensional dynamic system motion model construction and simulation method” was accepted by the State Intellectual Property Office of China. Through the construction and simulation of the motion model of a multi-level and multi-dimensional dynamic system, the motion trajectory of the motion factors in each dynamic system is nested and substituted into the next dynamic subsystem to establish the motion trajectory of the motion factors in its dynamic subsystem. Until the dynamic trajectory model of the motion factors in the minimum dynamic subsystem is obtained, the motion model of a multi-level and multi-dimensional dynamic system is constructed, which reveals the motion law that can unify the microscopic particles and all the motion factors in the macroscopic universe.

scholarly journals Quasi-optimal synthesis of an adaptive filter in the problem of estimating the state of dynamic systems

2020 ◽  
Vol 210 ◽  
pp. 01002
Author(s):  
Andrey Kostoglotov ◽  
Anton Penkov ◽  
Sergey Lazarenko
Keyword(s):  
Dynamic Systems ◽  
Degrees Of Freedom ◽  
Optimal Estimation ◽  
The State ◽  
System Model ◽  
Motion Model ◽  
Unknown Parameters ◽  
Generalized Lagrangian ◽  
Controlled Motion ◽  
Decomposition Principle

The problem of synthesis of filters to estimate the state of dynamical systems is considered based on the condition for the maximum of the generalized power function and stationarity of the generalized Lagrangian and Hamiltonian of the estimated system model. The paper demonstrates that the use of invariants in combination with the decomposition principle makes it possible to simplify the equations of controlled motion and reduce them to a system of independent equations in terms of the number of degrees of freedom. This approach reduces the number of unknown parameters of the motion model, which greatly simplifies the adaptation process when developing filters for quasi-optimal estimation of the state parameters of dynamic systems. Comparative analysis of the results of the mathematical simulation shows that the application of the proposed method increases the efficiency of filters of the Kalman structure.

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