Improved Maneuvering-Based Mathematical Model for Free-Running Ship Motions in Following Waves Using High-Fidelity CFD Results and System-Identification Technique

2019 ◽  
pp. 91-115 ◽  
Author(s):  
Motoki Araki ◽  
Hamid Sadat-Hosseini ◽  
Yugo Sanada ◽  
Naoya Umeda ◽  
Frederick Stern
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Ship Motions ◽  
High Fidelity ◽  
Identification Technique ◽  
Free Running

MICROCONTROLLER-BASED FOR SYSTEM IDENTIFICATION TOOLS USING LEAST SQUARE METHOD FOR RC CIRCUITS

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Ang Jia Yi ◽  
M. S. Abdul Majid ◽  
Azuwir M. N. ◽  
S. Yaacob
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Least Square Method ◽  
Least Square ◽  
Real Time System ◽  
System Identification Method ◽  
Identification Method ◽  
Verification Methods ◽  
Identification Technique ◽  
Rc Circuit

System identification is one of the method to construct a plant mathematical model from experimental data. This method has been widely applied in the automatic control, aviation, spaceflight medicine, society economics and other fields more. With the rapid growth of the science and technology, the system identification technique has increasingly grown in various applications. Since most of the system identification devices are off-line base, this means that the system identification can only be done after collecting the data and process through a computer devices. This paper will show how to process system identification method with real-time system. This method required a microcontroller as the medium to perform. That’s why the system identification method will be programmed into a microcontroller, based on Least Square Method. Later, the system will be tested on a RC circuit to see the effect of the signal and the mathematical model obtained. The data will undergo the system identification toolbox for process using ARX and ARMAX model. On the other hand, the data will also be collected using the microcontroller created for analysis purpose. To ensure the validity of the model some verification methods are performed. Results show that the Least Square Method using Microcontroller base has the capability to work as a system identification tools.

Estimation of Hydrodynamic Coefficients of a Nonlinear Manoeuvring Mathematical Model With Free-Running Ship Model Tests

2018 ◽  
Vol Vol 160 (A3) ◽  
Author(s):  
Haitong Xu ◽  
M A Hinostroza ◽  
C Guedes Soares
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Model Tests ◽  
Loss Functions ◽  
Identification Algorithm ◽  
Hydrodynamic Coefficients ◽  
Global Optimization Algorithm ◽  
Identification Process ◽  
Ship Model ◽  
Free Running

Free-running model tests have been carried out based on a scaled chemical tanker ship model, having a guidance, control and navigation system developed and implemented in LabVIEW. In order to make the modelling more flexible and physically more realistic, a modified version of Abkowitz model was introduced. During the identification process, the model’s structure is fixed and its parameters have been obtained using system identification. A global optimization algorithm has been used to search the optimum values and minimize the loss functions. In order to reduce the effect of noise in the variables, different loss functions considering the empirical errors and generalization performance have been defined and implemented in the system identification program. The hydrodynamic coefficients have been identified based on the manoeuvring test data of free-running ship model. Validations of the system identification algorithm were also carried out and the comparisons with experiments demonstrated the effectiveness of the proposed system identification method.

Design of a low-bandwidth position controller based on system identification for an electro-hydrostatic actuator

2017 ◽  
Vol 232 (2) ◽  
pp. 149-160
Author(s):  
Guangan Ren ◽  
Jinchun Song ◽  
Nariman Sepehri
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Positioning System ◽  
Quantitative Feedback Theory ◽  
Test Rig ◽  
Position Controller ◽  
Identification Technique ◽  
System Uncertainties ◽  
Physical Laws ◽  
Response Envelope

In order to design a controller, mathematical model is usually derived first, either from physical laws or by employing a system identification technique. Physical laws may not fully define the system because of the existing uncertainties and/or difficulty to accurately model certain phenomenon. Therefore, the resulting controller may be too conservative. In this article, we design a low-bandwidth controller for an electro-hydrostatic actuator positioning system based on a system identification technique. The designed controller is also linear, fixed-gain and robust to system uncertainties. A set of offline parametric linear identifications are performed under different conditions, including various environmental stiffnesses, levels of actuator internal leakage, viscous dampings and load masses. The obtained family of identified models is then used to design a quantitative feedback theory controller that satisfies given tracking and stability specifications. In addition, the performance of the controller is examined against another quantitative feedback theory controller that is designed for the same system using physical laws. The performances of two controllers are examined on a test rig. Experimental results show that both quantitative feedback theory controllers are capable of maintaining actuator position within acceptable response envelope. However, the controller designed based on physical laws has higher bandwidth and therefore is more conservative.

scholarly journals AN INTRODUCTION TO SISTEM IDENTIFICATION FOR A QUARTER CAR PASSIVE SUSPENSION

2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Endang Susanti
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Automatic Control ◽  
Rapid Development ◽  
Science And Technology ◽  
Marine Ecology ◽  
Passive Suspension ◽  
The Status ◽  
Identification Technique ◽  
Quarter Car

At present, as a method of establishing mathematical model of the system, the system identification has been widely applied to the automatic control, aviation, spaceflight, astronomy, medicine, biology, marine ecology and society, economics and many other fields. With the rapid development of science and technology, the status of system identification technique in various disciplines is becoming increasingly important. This paper introduces an system identification used for a quarter car passive suspension and a review previous research.

ESTIMATION OF HYDRODYNAMIC COEFFICIENTS OF A NONLINEAR MANOEUVRING MATHEMATICAL MODEL WITH FREE-RUNNING SHIP MODEL TESTS

2021 ◽  
Vol 160 (A3) ◽  
Author(s):  
Haitong Xu ◽  
M A Hinostroza ◽  
C Guedes Soares
Keyword(s):  
Mathematical Model ◽  
System Identification ◽  
Model Tests ◽  
Loss Functions ◽  
Identification Algorithm ◽  
Hydrodynamic Coefficients ◽  
Global Optimization Algorithm ◽  
Identification Process ◽  
Ship Model ◽  
Free Running

Free-running model tests have been carried out based on a scaled chemical tanker ship model, having a guidance, control and navigation system developed and implemented in LabVIEW. In order to make the modelling more flexible and physically more realistic, a modified version of Abkowitz model was introduced. During the identification process, the model’s structure is fixed and its parameters have been obtained using system identification. A global optimization algorithm has been used to search the optimum values and minimize the loss functions. In order to reduce the effect of noise in the variables, different loss functions considering the empirical errors and generalization performance have been defined and implemented in the system identification program. The hydrodynamic coefficients have been identified based on the manoeuvring test data of free-running ship model. Validations of the system identification algorithm were also carried out and the comparisons with experiments demonstrated the effectiveness of the proposed system identification method.

A System Identification Method for Excitation-Frequency Dependent Rotordynamic Coefficients

2012 ◽  
Author(s):  
Timothy W. Dimond ◽  
Amir A. Younan ◽  
Paul Allaire
Keyword(s):  
System Identification ◽  
Measurement Uncertainty ◽  
Excitation Frequency ◽  
Frequency Dependent ◽  
Rotordynamic Coefficients ◽  
Adjoint Systems ◽  
Dynamic Coefficients ◽  
Backward Whirl ◽  
Identification Technique ◽  
Damped Systems

Experimental identification of rotordynamic systems presents unique challenges. Gyroscopics, generally damped systems, and non-self-adjoint systems due to fluid structure interaction forces mean that symmetry cannot be used to reduce the number of parameters to be identified. Rotordynamic system experimental measurements are often noisy, which complicates comparisons with theory. When linearized, the resulting dynamic coefficients are also often a function of excitation frequency, as distinct from operating speed. In this paper, a frequency domain system identification technique is presented that addresses these issues for rigid-rotor test rigs. The method employs power spectral density functions and forward and backward whirl orbits to obtain the excitation frequency dependent effective stiffness and damping. The method is highly suited for use with experiments that employ active magnetic exciters that can perturb the rotor in the forward and backward whirl directions. Simulation examples are provided for excitation-frequency reduced tilting pad bearing dynamic coefficients. In the simulations, 20 and 50 percent Gaussian output noise was considered. Based on ensemble averages of the coefficient estimates, the 95 percent confidence intervals due to noise effects were within 1.2% of the identified value. The method is suitable for identification of linear dynamic coefficients for rotordynamic system components referenced to shaft motion. The method can be used to reduce the effect of noise on measurement uncertainty. The statistical framework can also be used to make decisions about experimental run times and acceptable levels of measurement uncertainty. The data obtained from such an experimental design can be used to verify component models and give rotordynamicists greater confidence in the design of turbomachinery.

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