Fundamentals of MATLAB Programming

2008 ◽  
pp. 25-60
Keyword(s):  
Matlab Programming

Simulation and Analysis of Two-Mass Suspension Modification Using MATLAB Programming

2019 ◽  
Vol 3 (1) ◽  
pp. 160-165
Author(s):  
Hendry D. Chahyadi
Keyword(s):  
Vibrational Energy ◽  
State Space Model ◽  
Mass System ◽  
Modeling And Analysis ◽  
The Road ◽  
Final Project ◽  
Quarter Car ◽  
Automotive Suspension ◽  
Mass Spring ◽  
Matlab Programming

The designs of automotive suspension system are aiming to avoid vibration generated by road condition interference to the driver. This final project is about a quarter car modeling with simulation modeling and analysis of Two-Mass modeling. Both existing and new modeling are being compared with additional spring in the sprung mass system. MATLAB program is developed to analyze using a state space model. The program developed here can be used for analyzing models of cars and vehicles with 2DOF. The quarter car modelling is basically a mass spring damping system with the car serving as the mass, the suspension coil as the spring, and the shock absorber as the damper. The existing modeling is well-known model for simulating vehicle suspension performance. The spring performs the role of supporting the static weight of the vehicle while the damper helps in dissipating the vibrational energy and limiting the input from the road that is transmitted to the vehicle. The performance of modified modelling by adding extra spring in the sprung mass system provides more comfort to the driver. Later on this project there will be comparison graphic which the output is resulting on the higher level of damping system efficiency that leads to the riding quality.

Five-Lump Kinetic Model for the Catalytic Cracking Process\

2018 ◽  
Vol 69 (10) ◽  
pp. 2633-2637
Author(s):  
Raluca Dragomir ◽  
Paul Rosca ◽  
Cristina Popa
Keyword(s):  
Kinetic Model ◽  
Programming Language ◽  
Catalytic Cracking ◽  
Computational Method ◽  
Industrial Data ◽  
New Model ◽  
Optimization And Control ◽  
Cracking Process ◽  
And Control ◽  
Matlab Programming

The main objectives of the present paper are to adaptation the five-kinetic model of the catalytic cracking process and simulation the riser to predicts the FCC products yields when one of the major input variable of the process is change. The simulation and adaptation are based on the industrial data from Romanian refinery. The adaptation is realize using a computational method from Optimization Toolbox from Matlab programming language. The new model can be used for optimization and control of FCC riser.

A Review of Different Types of DOE Methods as a Useful Platform for Improving the Performance of Nano Adsorbents in Removal Systems of Pollutants

2020 ◽  
Vol 10 (3) ◽  
pp. 219-227
Author(s):  
Ali Behmaneshfar ◽  
Abdolhossein Sadrnia ◽  
Hassan Karimi-Maleh
Keyword(s):  
Response Surface Methodology ◽  
Design Of Experiments ◽  
Web Of Science ◽  
Computer Software ◽  
Coefficient Of Determination ◽  
Design Expert ◽  
Number Of Factors ◽  
Different Types ◽  
Matlab Programming ◽  
Nano Adsorbent

Background: In recent years, the Design of Experiments (DOE) is used for removing pollutant from wastewater by nano-adsorbent. Some methods are Taguchi, Response Surface Methodology (RSM) and factorial design. The aim of this paper is to review different used methods of DOE in removing pollutant to suggest some notations to scholars. Methods: The reviewed papers were searched in Google Scholar, Scopus, and Web of Science randomly and categorized based on DOE methods. Results: Number of factors and responses in DOE for removing pollutants from wastewater are between 2-6 and 1-4, respectively. There are several computer software programs that provide simple use of these methods, such as Qualitek, Design Expert, Minitab, R and Matlab Programming. All models have a coefficient of determination R-sq more than 0.9. Conclusion: All the mentioned methods are appropriate because of the high R-sq value. Since the largest number of runs are used in RSM, it is not suitable for the experiments which are conducted by expensive materials and process. Furthermore, Design Expert and Minitab are the most popular software used by scholars in DOE methods for the removal of pollutant.

User Power Behavior Similarity Clustering Based on Unsupervised Extreme Learning Machine Algorithm

2020 ◽  
Vol 13 (5) ◽  
pp. 641-649
Author(s):  
Yuancheng Li ◽  
Yaqi Cui ◽  
Xiaolong Zhang
Keyword(s):  
Extreme Learning Machine ◽  
Clustering Algorithm ◽  
Characteristic Curve ◽  
Clustering Algorithms ◽  
Data Sets ◽  
Residential Areas ◽  
Processing Power ◽  
Learning Machine ◽  
Advanced Metering ◽  
Matlab Programming

Background: Advanced Metering Infrastructure (AMI) for the smart grid is growing rapidly which results in the exponential growth of data collected and transmitted in the device. By clustering this data, it can give the electricity company a better understanding of the personalized and differentiated needs of the user. Objective: The existing clustering algorithms for processing data generally have some problems, such as insufficient data utilization, high computational complexity and low accuracy of behavior recognition. Methods: In order to improve the clustering accuracy, this paper proposes a new clustering method based on the electrical behavior of the user. Starting with the analysis of user load characteristics, the user electricity data samples were constructed. The daily load characteristic curve was extracted through improved extreme learning machine clustering algorithm and effective index criteria. Moreover, clustering analysis was carried out for different users from industrial areas, commercial areas and residential areas. The improved extreme learning machine algorithm, also called Unsupervised Extreme Learning Machine (US-ELM), is an extension and improvement of the original Extreme Learning Machine (ELM), which realizes the unsupervised clustering task on the basis of the original ELM. Results: Four different data sets have been experimented and compared with other commonly used clustering algorithms by MATLAB programming. The experimental results show that the US-ELM algorithm has higher accuracy in processing power data. Conclusion: The unsupervised ELM algorithm can greatly reduce the time consumption and improve the effectiveness of clustering.

Improved Clustering Algorithm of Spatial Data Structure Based on Matlab Simulink

2014 ◽  
Vol 608-609 ◽  
pp. 98-102
Author(s):  
Shan Mei Xiong ◽  
Ru Lian Wu ◽  
Hui Wang
Keyword(s):  
Spatial Data ◽  
Clustering Algorithm ◽  
Geographical Location ◽  
Calculation Model ◽  
Space Structure ◽  
Urban Tourism ◽  
Programming Algorithm ◽  
Tourism Destination ◽  
Consumption Structure ◽  
Matlab Programming

This paper has introduced the clustering algorithm into the model of urban tourism destination consumption structure, and has used MATLAB programming algorithm to improve the calculation model of consumption structure for tourism destination, which has obtained the spatial data model of the consumption structure. The model roundly considers the influence of geographical location, cultural factors, political factors and economic factors, and it establishes new clustering algorithm model with four coefficients, and has realized the algorithm by the use of MATLAB programming. Finally, the consumption structure of the same destination in different provinces is calculated by using the spatial system model, which has obtained the calculation curve of consumption space structure and the clustering results, and has provided technical reference for the research on consumption of urban tourism destination.

Milling Force Prediction for Circular Contour Machining

2014 ◽  
Vol 800-801 ◽  
pp. 243-248
Author(s):  
Kai Zhao ◽  
Zhan Qiang Liu
Keyword(s):  
Prediction Model ◽  
Milling Process ◽  
Machining Process ◽  
Curvature Radius ◽  
Force Model ◽  
Milling Force ◽  
Circular Contour ◽  
The Mean ◽  
Contour Machining ◽  
Matlab Programming

When machining the complex parts of aircraft engines, the milling force for the circular contour must be accurately predicted to reduce machining vibration. In this paper, the prediction model of the mean milling force per tooth during machining circular contour is developed. Firstly, the formulas of the entry angle, the exit angle and the equivalent feed per tooth are established through the analysis of circular contour milling process. Then, the equation of the mean milling force per tooth is deduced based on mechanistic force model during the circular contour machining process. Finally, the prediction model of mean milling force per tooth during machining circular contour is developed using MATLAB programming. The relationship between the milling force per tooth and surface curvature radius of the machined workpiece is also analyzed in this paper.

scholarly journals An Improved Generalized Method for Evaluation of Parameters, Modeling, and Simulation of Photovoltaic Modules

2017 ◽  
Vol 2017 ◽  
pp. 1-19 ◽  
Author(s):  
Vandana Jha ◽  
Uday Shankar Triar
Keyword(s):  
Modeling And Simulation ◽  
Standard Test ◽  
Unknown Parameters ◽  
Photovoltaic Modules ◽  
Pv Module ◽  
Test Conditions ◽  
Pv Modules ◽  
Evaluation Of Parameters ◽  
Output Characteristics ◽  
Matlab Programming

This paper proposes an improved generalized method for evaluation of parameters, modeling, and simulation of photovoltaic modules. A new concept “Level of Improvement” has been proposed for evaluating unknown parameters of the nonlinear I-V equation of the single-diode model of PV module at any environmental condition, taking the manufacturer-specified data at Standard Test Conditions as inputs. The main contribution of the new concept is the improvement in the accuracy of values of evaluated parameters up to various levels and is based on mathematical equations of PV modules. The proposed evaluating method is implemented by MATLAB programming and, for demonstration, by using the values of parameters of the I-V equation obtained from programming results, a PV module model is build with MATLAB. The parameters evaluated by the proposed technique are validated with the datasheet values of six different commercially available PV modules (thin film, monocrystalline, and polycrystalline) at Standard Test Conditions and Nominal Operating Cell Temperature Conditions. The module output characteristics generated by the proposed method are validated with experimental data of FS-270 PV module. The effects of variation of ideality factor and resistances on output characteristics are also studied. The superiority of the proposed technique is proved.

scholarly journals Novel Analytical Method for Mix Design and Performance Prediction of High Calcium Fly Ash Geopolymer Concrete

Polymers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 900
Author(s):  
Chamila Gunasekara ◽  
Peter Atzarakis ◽  
Weena Lokuge ◽  
David W. Law ◽  
Sujeeva Setunge
Keyword(s):  
Compressive Strength ◽  
Fly Ash ◽  
Gradient Algorithm ◽  
Geopolymer Concrete ◽  
Statistical Regression ◽  
Solid Ratio ◽  
Marquardt Algorithm ◽  
High Calcium ◽  
High Calcium Fly Ash ◽  
Matlab Programming

Despite extensive in-depth research into high calcium fly ash geopolymer concretes and a number of proposed methods to calculate the mix proportions, no universally applicable method to determine the mix proportions has been developed. This paper uses an artificial neural network (ANN) machine learning toolbox in a MATLAB programming environment together with a Bayesian regularization algorithm, the Levenberg-Marquardt algorithm and a scaled conjugate gradient algorithm to attain a specified target compressive strength at 28 days. The relationship between the four key parameters, namely water/solid ratio, alkaline activator/binder ratio, Na2SiO3/NaOH ratio and NaOH molarity, and the compressive strength of geopolymer concrete is determined. The geopolymer concrete mix proportions based on the ANN algorithm model and contour plots developed were experimentally validated. Thus, the proposed method can be used to determine mix designs for high calcium fly ash geopolymer concrete in the range 25–45 MPa at 28 days. In addition, the design equations developed using the statistical regression model provide an insight to predict tensile strength and elastic modulus for a given compressive strength.

Automation of faulty type classification considering voltage sag and current swell profile by using MATLAB programming

2019 ◽  
Author(s):  
Lilik J. Awalin ◽  
Kanendra Naidu ◽  
Abdulkadir Suyono ◽  
Ibrahim Ali
Keyword(s):  
Voltage Sag ◽  
Matlab Programming ◽  
Type Classification
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