Parametric Identification Method for an Absorption Air Conditioning Parabolic Trough Collector Solar Plant

2020 ◽  
Vol 9 (4) ◽  
pp. 01
Author(s):  
Jorge Díaz - Salgado ◽  
Sandra García - López ◽  
Yuridiana R Galindo - Luna ◽  
R. J. Romero
Keyword(s):  
Mathematical Model ◽  
Air Conditioning ◽  
Least Squares Method ◽  
Flow Line ◽  
Parametric Identification ◽  
Unknown Parameters ◽  
Thermal Plant ◽  
Identification Method ◽  
Solar Plant ◽  
The Mathematical Model

In this work is established a parametric identification method for an absorption air conditioning solar plant. A scaled thermal plant, consisting of a thermal capacitor and a flow line that acts as a capacitor and thermal energy radiator is used. As the mathematical model of the scaled plant is structurally identical to that of the solar plant the first is used to determine the methodology that can be used later for the identification of the PTC solar plant. Parametric identification is a necessary step that allows to determine the unknown parameters of the mathematical model of any solar/thermal plant. This model then can be used to analyze the plant characteristics and design an appropriate control algorithm. Although the system model is nonlinear it can be expressed in the form of a linear regressor in the parameters. This permits to use the least squares method as the identification method. The method is applied to the thermal plant to identify the useful form that the covariance matrix and excitation signals should have to ensure that when applied to the solar plant its unknown parameters can be properly estimated. Once the solar plant parameters are properly estimated model can be used to analyze and simulate the operation of the absorption air conditioning system.

Research on Generator Excitation Parameter Identification - PSS Low-Pass Link Parameter Identification

2013 ◽  
Vol 805-806 ◽  
pp. 716-720
Author(s):  
Tao Xu ◽  
Tian Long Shao ◽  
Dong Fang Zhang
Keyword(s):  
Mathematical Model ◽  
Parameter Identification ◽  
Least Squares Method ◽  
Least Square Method ◽  
Least Square ◽  
National Standards ◽  
Matlab Software ◽  
Low Pass ◽  
Newton Iterations ◽  
The Mathematical Model

Combined with the contents of the study-PSS low-pass link parameter identification. Least-squares method is selected. Using least-square method for PSS low-pass link mathematical model are also deduced. For the results, because of the mathematical model is solving nonlinear equations, cannot used by the Newton method directly. So we choose to use Newton iterations, with this feature, choose to use MATLAB software to solve the equation. Identification of the use of MATLAB software lags after the PSS parameters obtained recognition results compared with national standards, identifying and verifying the practicability.

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.

Structure of Parametric Designing Simulation Platform of Automotive Air Conditioning Condenser

2012 ◽  
Vol 220-223 ◽  
pp. 689-692
Author(s):  
Yi Hua Ni ◽  
Hai Guo ◽  
Jian Wu ◽  
Jiang Xin Yang
Keyword(s):  
Mathematical Model ◽  
Air Conditioning ◽  
Heat Transfer Performance ◽  
Programming System ◽  
Transfer Performance ◽  
Operating Characteristics ◽  
Element Analysis ◽  
Automotive Air Conditioning ◽  
Element Simulation ◽  
The Mathematical Model

The physical and mathematical model of parallel flow automotive air condition condenser was built based on the analysis of its structure and operating characteristics; then the mathematical model was verified and optimized through finite element analysis and running experiments. The VB programming system was used to do Solidworks pro-development and condenser parameterization design module was built. Finally a condenser design and study platform facing to the heat transfer performance and structure with infinite element simulation and numerical simulation was realized.

Inverse Approach Using Bio-Inspired Algorithm Within Bayesian Framework for the Estimation of Heat Transfer Coefficients During Solidification of Casting

2019 ◽  
Vol 142 (1) ◽  
Author(s):  
P. S. Vishweshwara ◽  
N. Gnanasekaran ◽  
M. Arun
Keyword(s):  
Heat Transfer ◽  
Mathematical Model ◽  
Initial Conditions ◽  
Bayesian Framework ◽  
Simultaneous Estimation ◽  
Unknown Parameters ◽  
Single Experiment ◽  
Inverse Approach ◽  
Solidification Problem ◽  
The Mathematical Model

Abstract In any parameter estimation problem, it is desirable to obtain more information in one single experiment. However, it is difficult to achieve multiple objectives in one single experiment. The work presented in this paper is the simultaneous estimation of heat transfer coefficient parameters, latent heat, and modeling error during the solidification of Al–4.5 wt %Cu alloy with the aid of Bayesian framework as an objective function that harmoniously matches the mathematical model and measurements. A 1D transient solidification problem is considered to be the mathematical model/forward model and numerically solved to obtain temperature distribution for the known boundary and initial conditions. Genetic algorithm (GA) and particle swarm optimization (PSO) are used as an inverse approach and the estimation of unknown parameters is accomplished for both pure and noisy temperature data. The use of Bayesian framework for the estimation of unknown parameters not only provides the information about the uncertainties associated with the estimates but also there is an inherent regularization term in which the inverse problem boils down to well-posed problem thereby plethora of information is extracted with less number of measurements. Finally, the results of this work open up new prospects for the solidification problem so as to obtain a feasible solution with the present approach.

scholarly journals IMPLEMENTATION OF THE METHODS OF IDENTIFICATION OF STATIC CONTROL OBJECTS

2017 ◽  
pp. 72-78
Author(s):  
Sergey Pachkin ◽  
Sergey Pachkin ◽  
Roman Kotlyarov ◽  
Roman Kotlyarov
Keyword(s):  
Mathematical Model ◽  
Control System ◽  
Automatic Control ◽  
Automatic Control System ◽  
Mathematical Description ◽  
Control Object ◽  
Parametric Identification ◽  
Identification Problem ◽  
Temperature Control System ◽  
The Mathematical Model

One of the main tasks solved in the development of automatic control systems is the identification of the control object, which consists in obtaining its mathematical description. The nature and type of the mathematical model is determined by the goals and tasks for which it will be used. In the present case, the aim of obtaining the model is the synthesis of an automatic control system. Proceeding from the requirements of control problems, the identification problem consists in determining the structure and parameters of the mathematical model that ensure the best similarity of the model and object responses to the same input action. The article considers the experimental method of obtaining a mathematical description of the control object based on the results of measuring its input and output parameters and then processing the obtained results. The control object is the EP10 emulator made by the Oven Company, which is a miniature furnace. The emulator is used in experimental research in the process of commissioning using thermostat controls, and also applicable for educational purposes as part of training and research stands. As a result of structural identification with subsequent adjustment of the coefficients with the help of parametric identification, a model of the control object in the form of a second order aperiodic link is obtained. Parameters and type of the mathematical model allowed to make calculations and determine the parameters of adjustment of the TRM251 PID-controller. The software implementation of the automatic control system in the MatLAB environment made it possible to evaluate transient processes in a closed system. Thus, the calculation and analysis of the automatic control system in the first approximation were made. The final result can be obtained at the stage of commissioning the automatic temperature control system in the EP10 emulator using adaptation algorithms.

Estimation of State Variables in the Ćuk Converter Mathematical Model with Partially Unknown Parameters

2021 ◽  
Vol 22 (9) ◽  
pp. 451-458
Author(s):  
A. A. Bobtsov ◽  
R. Ortega ◽  
N. A. Nikolaev ◽  
O. V. Slita ◽  
O. A. Kozachek ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Finite Time ◽  
Control Algorithm ◽  
Power Converter ◽  
The State ◽  
Model Parameters ◽  
State Variables ◽  
Unknown Parameters ◽  
Proportional Integral ◽  
The Mathematical Model

In this paper the solution was proposed for the state variables estimation problem in the mathematical model of the DC switch-mode power converter built according to the Ćuk scheme. Pulse converters are one of the main components of most modern electrical devices and the circuit proposed by Slobodan Ćuk in the 70s of the 20th century is still relevant and demanded. Traditionally, PI (proportional-integral) controllers or proportional-integral adaptive control algorithm (PI-PBC), based on passification methods and superior to standard PI controllers in accuracy, are used as the control algorithm for power converters. However, you need to know the entire vector of the state variables of the converter to build a PI-PBC controller, and moreover, all its parameters must be accurately known. Unfortunately, in practice, such assumptions are not fulfilled, since parametric drifting is possible, and measurements of the converter’s state require additional sensors, which in some cases does not justify itself. Thus, there is a need to develop additional observers or estimators that allow obtaining data on all variables of the converter, as well as its parameters. The solution is based on the GPEBO method (generalized parameter estimation-based observers). The problem was solved under assumption that only the output signal (the output voltage of the converter) is measurable and some of the mathematical model parameters are unknown. An important aspect of the observer design is the development of an algorithm for unknown parameters and the state vector of a mathematical model estimation that ensures convergence in a finite time. Finite-time convergence is extremely important when designing observers since transients in pulse converters occur very quickly.

Mathematical modeling and parametric identification of a model using the example of a water-heating unit

2020 ◽  
Vol 42 (1) ◽  
pp. 103-109
Author(s):  
Sarsenbek Zhusupbekov ◽  
◽  
Laulasyn Abzhanova ◽  
Olzhas Nauryzbaev ◽  
◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Least Squares ◽  
Least Squares Method ◽  
Mimo System ◽  
Control Object ◽  
Real Object ◽  
Water Heating ◽  
Heating Unit ◽  
The Mathematical Model

The article is devoted to systemic issues related to the principles of mathematical modeling of technological objects, and the degree of adequacy of certain mathematical descriptions to real processes in these systems. In the article using the least squares method (least squares), a model of a water-heating unit is constructed as a MIMO system. The analysis of the process as a complex multi-connected control object. Based on the experimental data, a mathematical model is obtained in the state space of the water path. The adequacy of the mathematical model to the real object was established by directly comparing the output values of the object with the output values of the model. The results of a comparative assessment of the transition characteristics of the constructed mathematical model and the control object are presented. From the transient characteristics of the object and the mathematical model, it follows that the mathematical model fairly accurately and qualitatively describes the properties of the modeled object, i.e., it is adequate to the modeled object. The material presented allows you to teach a student to study processes by the method of mathematical modeling, including the preparation of a mathematical description, the choice of a solution method, software implementation of the model and verification of the model’s adequacy to a real object.

The Main Provisions of the Methodology for Assessing the Convergence of the Results of Mathematical Modeling of Continuous Processes of Avionics Devices and Field Experiments

2018 ◽  
Vol 19 (10) ◽  
pp. 680-688
Author(s):  
V. V. Slatin ◽  
M. A. Demkin ◽  
A. V. Golubkina
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Model ◽  
Measurement Errors ◽  
Field Experiments ◽  
Least Squares Method ◽  
Regression Line ◽  
Flight Tests ◽  
Continuous Processes ◽  
Statistical Hypotheses ◽  
The Mathematical Model

The questions of estimation of convergence of the processes received in single flight tests of an aviation complex and at mathematical modeling are considered. This evaluation is performed based on the methods of analysis of variance and means of verification of statistical hypotheses in decision-making on the convergence of the compared processes. For each of the compared processes, the least squares method determines the regression lines. By methods of mathematical statistics the permissible proximity of regression lines of the compared processes is established and the average regression line equivalent to the mathematical expectation of the analyzed statistical processes is determined. With respect to this line, the variance of deviations of the compared statistical processes is determined and their belonging to the General sample of processes is estimated. This suggests that under normal laws of the distribution of measurement errors there is an adequacy of the processes of the mathematical model of the stages of operation of the aviation complex and the observed processes of these stages during flight tests of the aviation complex under study.

Establishment and Analysis of Fault Model for the Central Air-Conditioning System

2012 ◽  
Vol 505 ◽  
pp. 112-115
Author(s):  
Lian You Li ◽  
Yong Jiang Shi ◽  
Dan Li
Keyword(s):  
Mathematical Model ◽  
Air Conditioning ◽  
Material Object ◽  
Air Conditioning System ◽  
Flow Noise ◽  
Air Cooler ◽  
Central Air Conditioning ◽  
Noise Vibration ◽  
The Mathematical Model ◽  
Fault Information

This paper analyzes the dynamic fault information (temperature, pressure, flow, noise, vibration etc.) in the process of operation of the air-conditioning system and establishes the simplified qualitative physical model which takes the surface air cooler as an example, and then writes out the mathematical model according to the simplified model. Finally, the paper gets some conclusions or conjecture suitable for the material object according to the research of the mathematical model.

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