scholarly journals Implementasi Sensor IMU untuk mengetahui Sudut Elevasi Kendaraan menggunakan Metode Least Square

2020 ◽  
Vol 8 (2) ◽  
pp. 301
Author(s):  
ERWANI MERRY SARTIKA ◽  
AUDYATI GANY ◽  
VINCENSIUS YUVENS
Keyword(s):  
Elevation Angle ◽  
Least Square Method ◽  
Absolute Error ◽  
Regression Equation ◽  
Least Square ◽  
Measurement Unit ◽  
Accelerometer Sensor ◽  
The Road ◽  
Acceleration Data ◽  
Input Acceleration

ABSTRAKKemiringan jalan menyebabkan pengendara sepeda motor lebih berhati-hati dalam mengendarai kendaraannya. Selain untuk keamanan, sudut elevasi jalan dapat mempengaruhi dalam pengendalian kendaraan sehingga dapat lebih menghemat energi. Pada paper ini sensor Inertial Measurement Unit (IMU) digunakan untuk mengetahui kemiringan kendaraan sepeda motor (naik/turun dan condong kiri/kanan). Dalam perancangannya beberapa data akselerasi dari sensor accelerometer IMU diolah dengan regresi sehingga diperoleh persamaan regresi yang kemudian digunakan untuk memperbanyak data sehingga data tersebut dapat digunakan untuk prediksi model antara 3 input nilai akselerasi dan 2 output nilai kemiringan sudut kendaraan. Prediksi model berhasil dengan indentifikasi menggunakan metode Least Square. Dari data pengamatan diperoleh bahwa rata-rata kesalahan absolut untuk kemiringan naik/turun dan condong kiri/kanan antara 5 o s/d 7 o, namun belum berhasil untuk sudut yang besar (70 o s/d 90 o).Kata kunci: IMU, accelerometer, sudut elevasi, Arduino, Least Square ABSTRACTThe slope of the road leads to awareness of motorcyclists ini riding their motorcycle addition to safety, the elevation angle of the road can affect vehicle control so that it can save more energy. In this paper the IMU sensor is used to determine the slope of a motorcycle (up / down and leaning left / right). In the design of some acceleration data from the IMU accelerometer sensor is processed so that the regression equation is obtained. The regression equation is used to generate the data to predict the model 3 input acceleration value and 2 output slope value of the vehicle. Model prediction was successful by identification using the Least Square method. Obtained from observational data that the average absolute error for the slope up / down and leaning left / right between 5 o to 7 o, but has not been successful for wide angles (70 o to 90 o).Keywords: IMU, accelerometer, elevation angle, Arduino, Least Square

scholarly journals System-Level Temperature Compensation Method for the RLG-IMU Based on HHO-RVR

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Hao Liang ◽  
Yumin Tao ◽  
Meijiao Wang ◽  
Yu Guo ◽  
Xingfa Zhao
Keyword(s):  
Least Square Method ◽  
Absolute Error ◽  
Performance Comparison ◽  
Compensation Method ◽  
Least Square ◽  
System Level ◽  
Measurement Unit ◽  
Error Terms ◽  
The Stability ◽  
Stability Time

The ring laser gyro inertial measurement unit has many systematic error terms and influences each other. These error terms show a complex nonlinear drift that cannot be ignored when the temperature changes, which seriously affects the stability time and output accuracy of the system. In this paper, a system-level temperature modeling and compensation method is proposed based on the relevance vector regression method. First, all temperature-related parameters are modeled; meanwhile, the Harris hawks optimization algorithm is used to optimize each model parameter. Then, the system compensation is modeled to stabilize the system output to the desired temperature. Compared with the least square method, the fitting performance comparison and the system dynamic compensation experiment prove this method’s superiority. The root mean square error, the mean absolute error, the R -squared, and the variance of residual increased by an average of 35.27%, 39.29%, 2.29%, and 30.34%, respectively.

Solar Tracking Device Based on Electronic Compass and Accelerometer

2014 ◽  
Vol 981 ◽  
pp. 522-525 ◽  
Author(s):  
Zhong Ran Zhang ◽  
Yuan Ma ◽  
Bo Jiao ◽  
Tong Liang Liu
Keyword(s):  
Elevation Angle ◽  
Least Square Method ◽  
Least Square ◽  
Stable Operation ◽  
Solar Tracking ◽  
High Flexibility ◽  
Tracking Device ◽  
Solar Position ◽  
Electronic Compass ◽  
The Magnetic Field

A solar tracking device was designed in this paper. First, In order to determine the initial direction of the mechanism and the east, HMC5883L was used for measuring the magnetic field of earth. Then, the mechanism began to operate according to the solar position which was confirmed though the astronomical calculation. Finally, the azimuth and the elevation angle of solar were measured and corrected by HMC5883L and MPU6050 respectively. HMC5883L was calibrated by the ellipse fitting, which was obtained though the least square method. The horizontal error of HMC5883L was compensated. The experimental study was performed. And the results show that the solar tracking device has the characteristics of stable operation, high flexibility and low requirement of installation precision.

scholarly journals Research on Antennas Alignment of Dynamic Point-to-Point Communication

2018 ◽  
Vol 2018 ◽  
pp. 1-5 ◽  
Author(s):  
Qilin Zeng ◽  
Jiaxin Liu ◽  
Weiming Xiong
Keyword(s):  
Elevation Angle ◽  
Least Square Method ◽  
Optimal Level ◽  
Least Square ◽  
Two Dimensional ◽  
Scanning Strategy ◽  
One Dimensional ◽  
Communication Signal ◽  
Signal Value ◽  
Point To Point

In the dynamic point-to-point communication, to track and aim at antenna fast and accurately is the guarantee of high quality communication signal. In order to solve the problem of antenna alignment, we used the least square method (LSM) to fit the optimal level signal value (LSV) point which is based on coordinate coarse tracking alignment and matrix scanning strategy to find the LSV in this paper. Antenna is driven by two-dimensional turntable (azimuth and elevation angle (AE)): the two-dimensional turntable is decomposed into two independent one-dimensional turntables, and the LSV in AE direction are obtained by scanning, respectively. The optimal LSV point of two-dimensional turntable can be find by combing optimal LSV point of two independent one-dimensional turntables. The method has the advantages of high precision and easy implementation and can meet the requirement of fast and accurately alignment in dynamic point-to-point communication antenna engineering.

A new method to reduce the noise of the miniaturised inertial sensors disposed in redundant linear configurations

2013 ◽  
Vol 117 (1188) ◽  
pp. 111-132 ◽  
Author(s):  
T. L. Grigorie ◽  
R. M. Botez
Keyword(s):  
Inertial Sensors ◽  
Inertial Sensor ◽  
Low Frequency ◽  
Minimum Variance ◽  
Measurement Unit ◽  
Time Step ◽  
Accelerometer Sensor ◽  
Sensor Model ◽  
Input Acceleration

Abstract This paper presents a new adaptive algorithm for the statistical filtering of miniaturised inertial sensor noise. The algorithm uses the minimum variance method to perform a best estimate calculation of the accelerations or angular speeds on each of the three axes of an Inertial Measurement Unit (IMU) by using the information from some accelerometers and gyros arrays placed along the IMU axes. Also, the proposed algorithm allows the reduction of both components of the sensors’ noise (long term and short term) by using redundant linear configurations for the sensors dispositions. A numerical simulation is performed to illustrate how the algorithm works, using an accelerometer sensor model and a four-sensor array (unbiased and with different noise densities). Three cases of ideal input acceleration are considered: 1) a null signal; 2) a step signal with a no-null time step; and 3) a low frequency sinusoidal signal. To experimentally validate the proposed algorithm, some bench tests are performed. In this way, two sensors configurations are used: 1) one accelerometers array with four miniaturised sensors (n = 4); and 2) one accelerometers array with nine miniaturised sensors (n = 9). Each of the two configurations are tested for three cases of input accelerations: 0ms−1, 9·80655m/s2 and 9·80655m/s2.

Research of Binocular Positioning Mathematical Model Based on the Least Square Method

2011 ◽  
Vol 50-51 ◽  
pp. 473-477 ◽  
Author(s):  
Chun Feng Liu ◽  
Xiao Li Meng ◽  
Huan Cheng Zhang
Keyword(s):  
Relative Position ◽  
Three Dimensional ◽  
Digital Camera ◽  
Least Square Method ◽  
Absolute Error ◽  
Least Square ◽  
Specific Data ◽  
Centroid Algorithm ◽  
Three Dimensional Coordinate ◽  
The Relationship

By giving a centroid algorithm to extract pixel coordinates of each circle in the center of a circle under the coordinates, through the coordinate transformation the image coordinates can be obtained. Based on the data obtained from above to verify the model, from the specific data of the relative error, absolute error and error propagation theory to discuss the algorithm accuracy and stability. Finally using the least square method, according to the mean square error criteria for the establishment of a minimum of three-dimensional coordinate system fixed relative position of two cameras, binocular positioning mathematical models and by discussing the nature of matrix and the relationship between the relative position of the camera to calibrate the binocular digital camera.

scholarly journals A regression approach for prediction of Youtube views

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Lau Tian Rui ◽  
Zehan Afizah Afif ◽  
R. D. Rohmat Saedudin ◽  
Aida Mustapha ◽  
Nazim Razali
Keyword(s):  
Least Square Method ◽  
Absolute Error ◽  
Descent Method ◽  
Least Square ◽  
Gradient Descent Method ◽  
Ordinary Least Square ◽  
The Public ◽  
Dependent Variables ◽  
Regression Approach ◽  
The Mean

YouTube has grown to be the number one video streaming platform on Internet and home to millions of content creator around the globe. Predicting the potential amount of YouTube views has proven to be extremely important for helping content creator to understand what type of videos the audience prefers to watch. In this paper, we will be introducing two types of regression models for predicting the total number of views a YouTube video can get based on the statistic that are available to our disposal. The dataset we will be using are released by YouTube to the public. The accuracy of both models are then compared by evaluating the mean absolute error and relative absolute error taken from the result of our experiment. The results showed that Ordinary Least Square method is more capable as compared to the Online Gradient Descent Method in providing a more accurate output because the algorithm allows us to find a gradient that is close as possible to the dependent variables despite having an only above average prediction.

scholarly journals Quality Evaluation of Wind Turbine Roller Bearing Profile in the Ultra-long Flexible Blade

2021 ◽  
Vol 251 ◽  
pp. 03082
Author(s):  
Mingshu Li ◽  
Yuhong Sun ◽  
Ling Wang ◽  
Zhiteng Gao
Keyword(s):  
Wind Turbine ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Roller Bearing ◽  
Least Square Method ◽  
Absolute Error ◽  
Least Square ◽  
Roller Profile ◽  
Quality Evaluation Model

In order to accurately measure and evaluate the quality of the roller profile of the ultra-long flexible blade bearing, an error evaluation model is established for the arc segment and the straight segment of the roller based on the least square method, and then an overall quality evaluation model is proposed based on these two error models. Through the simulation of a standard wind turbine cylindrical roller bearing, it is found that the quality evaluation model established in this work can effectively measure and evaluate the contour line of the wind turbine bearing’s roller. The overall absolute error is 0.0319 mm, which is consistent with the set random error. The overall quality evaluation model is also valid for other types of bearings commonly used in the wind turbine, which include arc and straight segments, and can be used to evaluate the error quality of the roller profile of wind turbine bearings.

Radar Estimation of the Height of a Cruising Aircraft

1979 ◽  
Vol 32 (3) ◽  
pp. 352-356 ◽  
Author(s):  
S. Nagaoka ◽  
E. Yoshioka ◽  
P. T. Muto
Keyword(s):  
Traffic Control ◽  
Elevation Angle ◽  
Three Dimensional ◽  
Least Square Method ◽  
General Concept ◽  
Least Square ◽  
Acquisition Time ◽  
Curve Fitting Method ◽  
Separation Standards ◽  
Navigation Accuracy

Separation standards are used for assuring the safe and effective operation of aircraft in a traffic control environment and as aircraft operations increase in number the need to reconsider separation standards is strongly voiced both by operators and controllers. A panel, the Review of the General Concept of Separation Panel (RGCSP), has been organized by ICAO and the possibility of reducing conventional separation standards has been discussed. Mathematical models for estimating collision risk due to loss of separation between aircraft require data on navigation accuracy. In general, three-dimensional radars are used for height finding but these are complicated and expensive.The altitude of the cruising aircraft is required within about 100 ft. In the simplified radar here described a rotating antenna produces a fan beam for scanning aircraft flying overhead. The data obtained from several scans are processed by a mini-computer and the height of the aircraft estimated by a least-square method and sequential approximation. Between the items of information obtained for each scan (the distance, the elevation angle and the data acquisition time) a theoretical relationship is established as an observation equation, one of the coefficients of which includes the height information. The coefficient is determined by a curve-fitting method. The paper first describes the method of analysis for height estimation and then an evaluation of the accuracy of the method by a computer simulation.

Identification of topology changes in power grids via reduced admittance matrix

2021 ◽  
Author(s):  
Ling Lin ◽  
Li Ding ◽  
Zhengmin Kong ◽  
Chaoyang Chen
Keyword(s):  
Power Systems ◽  
Power Grid ◽  
Measurement Data ◽  
Least Square Method ◽  
Least Square ◽  
Measurement Unit ◽  
Stable Operation ◽  
Admittance Matrix ◽  
Topology Changes ◽  
Grid Topology

Frequent changes in power grid topology bring risks to the stable operation of power systems. It is essential to identify changes in the power grid topology quickly and accurately. This paper presents a novel method named network reduction-based topology change identification (NR-TCI) algorithm to identify topology changes in multi-machine power systems. The proposed algorithm can quickly identify power grid topology changes using only phasor measurement unit (PMU) data sampled during the system’s transient process. The NR-TCI algorithm uses the network order reduction method to reduce the order of a bus admittance matrix and then uses PMU measurement data to estimate the reduced admittance matrix by least square method. Finally, the reduced admittance matrix is adopted to find topological information, and the Sherman–Morrison formula is utilized to identify the topology changes. The effectiveness of the proposed NR-TCI algorithm is verified with a case study of a 3 machine 9 bus system in Matlab. In addition, the influence of PMU sampling frequency on the effectiveness of the proposed algorithm is also studied.

scholarly journals Nonlinear regression analysis of length growth in cultured rainbow trout

2020 ◽  
Vol 72 (5) ◽  
pp. 1778-1788
Author(s):  
P.C. Janampa-Sarmiento ◽  
R. Takata ◽  
T.M. Freitas ◽  
M.M.B. Pereira ◽  
L. Sá-Freire ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Logistic Model ◽  
Performance Metrics ◽  
Model Performance ◽  
Least Square Method ◽  
Absolute Error ◽  
Small Sample ◽  
Least Square ◽  
Von Bertalanffy ◽  
Length Growth

ABSTRACT Length growth as a function of time has a non-linear relationship, so nonlinear equations are recommended to represent this kind of curve. We used six nonlinear models to calculate the length gain of rainbow trout (Oncorhynchus mykiss) during the final grow-out phase of 98 days under three different feed types in triplicate groups. We fitted the von Bertalanffy, Gompertz, Logistic, Brody, Power Function, and Exponential equations to individual length-at-age data of 900 fish. Equations were fitted to the data based on the least square method using the Marquardt iterative algorithm. Accuracy of the fitted models was evaluated using a model performance metrics combining mean squared residuals (MSR), mean absolute error (MAE) and Akaike's Information Criterion corrected for small sample sizes (AICc). All models converged in all cases tested. Evaluation criteria for the Logistic model indicated the best overall fit (0.67 of combined metric MSR, MAE and AICc) under all different feeding types, followed by the Exponential model (0.185), and the von Bertalanffy and Brody model (0.074, respectively). Additionally, ∆AICc results identify the Logistic and Gompertz models as being substantially supported by the data in 100% of cases. The logistic model can be suggested for length growth prediction in aquaculture of rainbow trout.

Sign in / Sign up

Export Citation Format

Share Document