scholarly journals Identification Method of SUAV in Diving Phase Based on Flight Tests

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Tieying Jiang ◽  
Junjie Yin ◽  
Chengwei Yang ◽  
Liang Jiang
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Moving Average ◽  
Flight Test ◽  
Installation Space ◽  
Flying Height ◽  
Autoregressive Moving Average ◽  
Identification Method ◽  
Aerial Vehicle

A mathematical model of the dive phase is an important research content for improving the accuracy of terminal control in the small unmanned aerial vehicle. The acquisition of the diving model poses new challenges, such as the small installation space, ultra-low flying height of small suicide drones, short flight time, strong coupling, less observable measurement, and elastic deformation of the wings during the drone dive phase. Based on the autoregressive moving average method, a multi-input multioutput noise term topology mathematical model is proposed in this paper. Through an improved least squares identification method, the diving model in the flight test is analyzed and verified. The identification results of the diving model obtained by the proposed method are compared with the least squares method dive model. The results indicate that the mathematical model and identification method proposed in this paper can effectively obtain the parameters of the drone dive model.

scholarly journals Data Filtering Based Recursive Least Squares Algorithm for Two-Input Single-Output Systems with Moving Average Noises

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Xianling Lu ◽  
Wei Zhou ◽  
Wenlin Shi
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Moving Average ◽  
Recursive Least Squares ◽  
Noise Model ◽  
Autoregressive Moving Average ◽  
Data Filtering ◽  
Noise Transfer Function ◽  
Single Output ◽  
Recursive Least Squares Method

This paper studies identification problems of two-input single-output controlled autoregressive moving average systems by using an estimated noise transfer function to filter the input-output data. Through data filtering, we obtain two simple identification models, one containing the parameters of the system model and the other containing the parameters of the noise model. Furthermore, we deduce a data filtering based recursive least squares method for estimating the parameters of these two identification models, respectively, by replacing the unmeasurable variables in the information vectors with their estimates. The proposed algorithm has high computational efficiency because the dimensions of its covariance matrices become small. The simulation results indicate that the proposed algorithm is effective.

Partially-coupled least squares based iterative parameter estimation for multi-variable output-error-like autoregressive moving average systems

2019 ◽  
Vol 13 (18) ◽  
pp. 3040-3051 ◽  
Author(s):  
Hao Ma ◽  
Jian Pan ◽  
Feng Ding ◽  
Ling Xu ◽  
Wenfang Ding
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Moving Average ◽  
Autoregressive Moving Average ◽  
Output Error

scholarly journals The identification of a device based on a Peltier element by the least squares method

2020 ◽  
pp. 17-27
Author(s):  
Vladimir Grinkevich ◽  
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Control Object ◽  
Object Identification ◽  
Model Parameters ◽  
Peltier Element ◽  
Transport Delay ◽  
Non Linear ◽  
The Mathematical Model

The evaluation of the mathematical model parameters of a non-linear object with a transport delay is considered in this paper. A temperature controlled stage based on a Peltier element is an identification object in the paper. Several input signal implementations are applied to the input of the identification object. The least squares method is applied for the calculation of the non-linear differential equitation parameters which describe the identification object. The least squares method is used due to its simplicity and the possibility of identification non-linear objects. The parameters values obtained in the process of identification are provided. The plots of temperature changes in the temperature control system with a controller designed based on the mathematical model of the control object obtained as a result of identification are shown. It is found that the mathematical model obtained in the process of identification may be applied to design controllers for non-linear systems, in particular for a temperature stage based on a Peltier element, and for self-tuning controllers. However, the least square method proposed in the paper cannot estimate the transport delay time. Therefore it is required to evaluate the time delay by temperature transient processes. Dynamic object identification is applied when it is required to obtain a mathematical model structure and evaluate the parameters by an input and output control object signal. Also, identification is applied for auto tuning of controllers. A mathematical model of a control object is required to design the controller which is used to provide the required accuracy and stability of control systems. Peltier elements are applied to design low-power and small- size temperature stage . Hot benches based on a Peltier element can provide the desired temperature above and below ambient temperature.

THE FLOW FIELD ACTING ON THE FLUTTERING PROFILE, KINEMATICS, FORCES AND TOTAL MOMENT

2013 ◽  
Vol 13 (07) ◽  
pp. 1340009 ◽  
Author(s):  
JAN KOZÁNEK ◽  
VÁCLAV VLČEK ◽  
IGOR ZOLOTAREV
Keyword(s):  
Mathematical Model ◽  
Least Squares ◽  
High Speed ◽  
Least Squares Method ◽  
High Speed Camera ◽  
Aerodynamic Forces ◽  
Total Moment ◽  
Airfoil Surface ◽  
Measured System ◽  
Simplified Mathematical Model

A high speed camera was used for interferometry visualization (in different phases of the motion) of the fluttering NACA0015 profile supported in a translational and rotational manner. First, the simplified mathematical model of the support of investigated profile was identified from minimum least squares differences between modeled and measured system responses. A special graphical Matlab procedure was proposed for evaluation of interferograms. Kinematic analysis defining motion of the profile as a function of time was obtained by a regression using the least squares method. Numerical integration of pressure functions around the airfoil surface allows for calculation of the resulting aerodynamic forces and moments.

MEMS Gyro Random Drift Model Parameter Identification Based on Two-Stage Recursive Least Squares Method

2012 ◽  
Vol 220-223 ◽  
pp. 1044-1047 ◽  
Author(s):  
Zhao Hua Liu ◽  
Jia Bin Chen ◽  
Yu Liang Mao ◽  
Chun Lei Song
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Moving Average ◽  
Recursive Least Squares ◽  
Model Parameters ◽  
Random Drift ◽  
Two Stage ◽  
Autoregressive Moving Average Model ◽  
Drift Model ◽  
Recursive Least Squares Method

Autoregressive moving average model (ARMA) was usually used for gyro random drift modeling. Because gyro random drift was a non-stationary, weak non-linear and time-variant random signal, model parameters were random and time-variant, too. For improving precision of gyro and reducing effects of random drift, this paper adopted two-stage recursive least squares method for ARMA parameter estimation. This method overcame the shortcomings of the conventional recursive extended least squares (RELS) algorithm. At the same time, the forgetting factor was introduced to adapt the model parameters change. The simulation experimental results showed that this method is effective.

Model Parameter Identification and Simulation of Ship Power System Based on Recursive Least Squares Method

2012 ◽  
Vol 220-223 ◽  
pp. 482-486 ◽  
Author(s):  
Jin Hui Hu ◽  
Da Bin Hu ◽  
Jian Bo Xiao
Keyword(s):  
Mathematical Model ◽  
Power Systems ◽  
Parameter Identification ◽  
Least Squares ◽  
Least Squares Method ◽  
Recursive Least Squares ◽  
Design Parameters ◽  
Model Parameters ◽  
Model Parameter ◽  
Model Parameter Identification

According to the lack of the part of the equipment design parameters of a certain type of ship power systems, the algorithm of recursive least squares for model parameter identification is studied. The mathematical model of the propulsion motor is established. The model parameters are calculated and simulated based on parameter identification method of recursive least squares. The simulation results show that a more precise mathematical model can be simple and easily obtained by using of the method.

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