Mathematical Model, Simulation, and Experimental Calibration of Electrostatic Wear-Site Sensor

2017 ◽  
Vol 17 (8) ◽  
pp. 2428-2438 ◽  
Author(s):  
Liu Ruochen ◽  
Zuo Hongfu
Keyword(s):  
Mathematical Model ◽  
Model Simulation ◽  
Experimental Calibration

Design of Control of DC Motor

2014 ◽  
Vol 611 ◽  
pp. 325-331
Author(s):  
Ľubica Miková ◽  
Michal Kelemen ◽  
Vladislav Maxim ◽  
Jaromír Jezný
Keyword(s):  
Mathematical Model ◽  
Virtual Environment ◽  
Computer Technology ◽  
Current Practice ◽  
Scientific Literature ◽  
Model Simulation ◽  
Graphical Interface ◽  
Dc Motors ◽  
Matlab Program ◽  
Simulation Results

In current practice the use of mathematical models is substantially widespread, reason being the recent increase in development of programs for this purpose, with the option of model simulation in a virtual environment, proportional to the evolving computer technology. The article contains a mathematical model created using Matlab program. The simulation results are compared with scientific literature that addresses DC motors and evaluated. For simplicity, a graphical interface was created.

An enhanced composting process with bioaugmentation: Mathematical modelling and process optimization

2021 ◽  
pp. 0734242X2110337
Author(s):  
Tea Sokač ◽  
Anita Šalić ◽  
Dajana Kučić Grgić ◽  
Monika Šabić Runjavec ◽  
Marijana Vidaković ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Model Simulation ◽  
Process Conditions ◽  
Air Flow Rate ◽  
Optimal Process ◽  
Composting Process ◽  
Different Types ◽  
Adiabatic Reactor ◽  
The Mathematical Model ◽  
Good Agreement

In this paper, two different types of biowaste composting processes were carried out – composting without and with bioaugmentation. All experiments were performed in an adiabatic reactor for 14 days. Composting enhanced with bioaugmentation was the better choice because the thermophilic phase was achieved earlier, making the composting time shorter. Additionally, a higher conversion of substrate (amount of substrate consumed) was also noticed in the process enhanced by bioaugmentation. A mathematical model was developed and process parameters were estimated in order to optimize the composting process. Based on good agreement between experimental data and the mathematical model simulation results, a three-level-four-factor Box-Behnken experimental design was employed to define the optimal process conditions for further studies. It was found that the air flow rate and the mass fraction of the substrate have the most significant effect on the composting process. An improvement of the composting process was achieved after altering the mentioned variables, resulting in shorter composting time and higher conversion of the substrate.

Real-Time Implementation for Tuning PID Controller Based on Advanced Optimization Techniques for Micro-Robotics System

2021 ◽  
Vol 10 (6) ◽  
pp. 161-173
Author(s):  
Ehab S. Ghith ◽  
◽  
Mohamed Sallam ◽  
Islam S. M. Khalil ◽  
Mohamed Serry ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Pid Controller ◽  
Model Simulation ◽  
Search Algorithm ◽  
Optimization Techniques ◽  
Control Technique ◽  
Flower Pollination Algorithm ◽  
Labview Software ◽  
Laboratory Setup ◽  
Sine Cosine Algorithm

The process of tuning the PID controller’s parameters is considered to be a difficult task. Several approaches were developed in the past known as conventional methods. One of these methods is the Ziegler and Nichols that relies on accurate mathematical model of the linear system, but if the system is complex the former method fails to compute the parameters of PID controller. To overcome this problem, recently there exist several techniques based on artificial intelligence such as optimization techniques. The optimization techniques does not require any mathematical model and they are considered to be easy to implement on any system even if it complex, can reach optimal solutions on the parameters. In this study, a new approach to control the position of the micro-robotics system proportional - integral - derivative (PID) controller is designed and a recently developed algorithm based on optimization is known as the sparrow search algorithm (SSA). By using the sparrow search algorithm (SSA), the optimal PID controller parameters were obtained by minimizing a new objective function, which consists of the integral square Time multiplied square Error (ISTES) performance index. The effectiveness of the proposed SSA-based controller was verified by comparisons made with the Sine Cosine algorithm (SCA), and Flower pollination algorithm (FPA) controllers in terms of time and frequency response. Each control technique will be applied to the identified model (simulation results) using MATLAB Simulink and the laboratory setup (experimental results) using LABVIEW software. Finally, the SSA showed the highest performance in time and frequency responses.

Stability Analysis of a Mathematical Model for Glioma-Immune Interaction under Optimal Therapy

2019 ◽  
Vol 20 (3-4) ◽  
pp. 269-285 ◽  
Author(s):  
Subhas Khajanchi
Keyword(s):  
Mathematical Model ◽  
Optimal Control ◽  
Stability Analysis ◽  
Model Simulation ◽  
Equilibrium Points ◽  
Glioma Cells ◽  
Adjoint System ◽  
Cellular Immunotherapy ◽  
Theory Of Optimal Control ◽  
Malignant Glioma Cells

AbstractWe investigate a mathematical model using a system of coupled ordinary differential equations, which describes the interplay of malignant glioma cells, macrophages, glioma specific CD8+T cells and the immunotherapeutic drug Adoptive Cellular Immunotherapy (ACI). To better understand under what circumstances the glioma cells can be eliminated, we employ the theory of optimal control. We investigate the dynamics of the system by observing biologically feasible equilibrium points and their stability analysis before administration of the external therapy ACI. We solve an optimal control problem with an objective functional which minimizes the glioma cell burden as well as the side effects of the treatment. We characterize our optimal control in terms of the solutions to the optimality system, in which the state system coupled with the adjoint system. Our model simulation demonstrates that the strength of treatment $u_{1}(t)$ plays an important role to eliminate the glioma cells. Finally, we derive an optimal treatment strategy and then solve it numerically.

ESTABLISHING OF THE SPATIAL DISTRIBUTION OF DISPOSABLE GROUNDWATER RESOURCES BY MULTI-CRITERIA ANALYSIS METHOD

2018 ◽  
Vol 471 ◽  
pp. 137-146
Author(s):  
Andrzej RODZOCH ◽  
Dominik MIAZ ◽  
Grzegorz JELENIEWICZ
Keyword(s):  
Mathematical Model ◽  
Spatial Distribution ◽  
Model Simulation ◽  
Groundwater Resources ◽  
Analysis Method ◽  
Control Data ◽  
Output Control ◽  
Input And Output ◽  
Management Area

A hydrogeologist often faces a serious difficulty in estimation of available groundwater resources. In contrast to renewable water resources, which are valuable for a study area and estimated with greater or lower precision depending on the quality of available data, disposable groundwater resources cannot be treated as a natural and relatively constant characteristic of the management area, because their size and spatial distribution depend on criteria assumed to set an optimal way for managing water supplies. Since those criteria can be defined in various ways and their significance can vary as well, spatial distribution of groundwater resources and their size can theoretically have infinite number of equally correct solutions. They can be only treated as optimal for a strictly specified set of criteria and therefore can be modified according to different needs and assumed priorities. Interpreted this way, they can only be calculated by the use of model simulation, because only a mathematical model is an effective tool for making such multi-criteria analyses. The paper presents an approach for setting criteria that limit the input and output control data, applied by HYDREKO in the process of spatial distribution of disposable groundwater resources. An example of use of this method is presented for the management area P-XVIII Dolna Warta (Rodzoch et al., 2017).

Mathematical Simulation of Hydraulic Power Pulse Machine at Matlab

2016 ◽  
Vol 685 ◽  
pp. 240-243 ◽  
Author(s):  
M.V. Novoseltseva ◽  
E.N. Pashkov ◽  
I.A. Masson
Keyword(s):  
Mathematical Model ◽  
Mathematical Simulation ◽  
Model Simulation ◽  
General Idea ◽  
Restriction Factors ◽  
Hydraulic Power ◽  
Power Pulse ◽  
Machine Operation ◽  
Simulation Results

General idea of mathematical simulation is set. Equations that describe hydraulic power pulse machine operation are described. Restriction factors are identified; they are included in mathematical model simulation. Mathematical simulation results are shown for essential parts of machine. Results of hydraulic power pulse machine mathematical simulation are presented.

A Research Based on the Deep Self-Balanced Hydraulic Pump

2011 ◽  
Vol 305 ◽  
pp. 411-415
Author(s):  
Bao De Jing ◽  
Bin Bin Lv ◽  
Zeng Jun Pan ◽  
Long Yi ◽  
Zhu Ge Gang ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Sea Water ◽  
Model Simulation ◽  
Water Pump ◽  
Technology Research ◽  
Hydraulic Pump ◽  
Pump Housing ◽  
The Status ◽  
Water Hydraulic ◽  
Simulation Results

The article will give information about the status of sea water pump technology research, carry out the analysis of the water pump slipper, piston and water pump housing and other key parts of hydraulic pumps, and finally make some optimization and innovation. In addition, there will be a mathematical model simulation for four major friction of the hydraulic pump sea water through the MatLab . The simulation results of the design of water hydraulic pump has a certain significance.

scholarly journals A Mathematical Model for Predicting the Winnowing Efficiency of Bambara Groundnut Sheller

2020 ◽  
Vol 5 (2) ◽  
pp. 225-228
Author(s):  
Inimfon Samuel Ossom ◽  
Akindele Folarin Alonge ◽  
Kingsley Charles Umani ◽  
Edidiong J. Bassey
Keyword(s):  
Experimental Data ◽  
Mathematical Model ◽  
Moisture Content ◽  
Model Equation ◽  
Model Simulation ◽  
Least Square Method ◽  
Bambara Groundnut ◽  
Least Square ◽  
Predicted Model ◽  
Experimental Values

A mathematical model for predicting the winnowing efficiency of bambara groundnut sheller was developed. The regression equation for model simulation was developed using Least Square Method. The model was verified and validated by fitting it into established experimental data from winnowing efficiency of already existed Bambara groundnut sheller. The result revealed that the fitted model correlated well with the experimental data with R-square value of 0.99. The winnowing efficiency obtained from the predicted model was approximately the same values with the experimental values. Therefore, the model equation was considered to be reasonably good for predicting the winnowing efficiency of bambara groundnut sheller for known values of moisture content and blower speed.

scholarly journals Analysis of Digital Twin Definition and Its Difference from Simulation Modelling in Practical Application

2020 ◽  
Author(s):  
I.I. Krasikov ◽  
A. N. Kulemin
Keyword(s):  
Mathematical Model ◽  
Model Simulation ◽  
Simulation Modelling ◽  
Practical Application ◽  
Product Lifecycle ◽  
Digital Twin ◽  
Common Definition ◽  
Model And Simulation ◽  
Digital Twins ◽  
Definition Of

The digital twin is widely known as a tool for digitalization of a product, but there is no common definition concerning this term. This article discusses the definition and utilization of digital twin. Areas of use, it’s implementation in the product lifecycle and most importantly it’s benefits. The lack of a standardized concept of a digital  twin leads to a misunderstanding between mathematical models and digital twin. Several definitions of digital twin were analyzed and compared with the definition of mathematical model and simulation modelling. The basic concept of areas of use for digital twin is introduced. The differences and similarities between the two definitions were found. The article aims first of all to help the management of digital twins in practical application. Keywords: Digital twin, Mathematical modelling, Mathematical model, Lifecycle of a product, Simulation modelling, Practical use of digital twin, Difference between the digital twin and mathematical model, Simulation.

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