Search results for: Parameter tuning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1279

Search results for: Parameter tuning

1039 A Dynamic Model of Air Pollution, Health,and Population Growth Using System Dynamics: A Study on Tehran-Iran (With Computer Simulation by the Software Vensim)

Authors: Keyvan Shahgholian, Hamid Hajihosseini

Abstract:

The significance of environmental protection is wellknown in today's world. The execution of any program depends on sufficient knowledge and required familiarity with environment and its pollutants. Taking advantage of a systematic method, as a new science, in environmental planning can solve many problems. In this article, air pollution in Tehran and its relationship with health and population growth have been analyzed using dynamic systems. Firstly, by using casual loops, the relationship between the parameters effective on air pollution in Tehran were taken into consideration, then these casual loops were turned into flow diagrams [6], and finally, they were simulated using the software Vensim [16]in order to conclude what the effect of each parameter will be on air pollution in Tehran in the next 10 years, how changing of one or more parameters influences other parameters, and which parameter among all other parameters requires to be controlled more.

Keywords: Air pollutions, Simulation, System Dynamics, Tehran, Vensim.

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1038 A Diffusion Least-Mean Square Algorithm for Distributed Estimation over Sensor Networks

Authors: Amir Rastegarnia, Mohammad Ali Tinati, Azam Khalili

Abstract:

In this paper we consider the issue of distributed adaptive estimation over sensor networks. To deal with more realistic scenario, different variance for observation noise is assumed for sensors in the network. To solve the problem of different variance of observation noise, the proposed method is divided into two phases: I) Estimating each sensor-s observation noise variance and II) using the estimated variances to obtain the desired parameter. Our proposed algorithm is based on a diffusion least mean square (LMS) implementation with linear combiner model. In the proposed algorithm, the step-size parameter the coefficients of linear combiner are adjusted according to estimated observation noise variances. As the simulation results show, the proposed algorithm considerably improves the diffusion LMS algorithm given in literature.

Keywords: Adaptive filter, distributed estimation, sensor network, diffusion.

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1037 Optimization of Copper-Water Negative Inclination Heat Pipe with Internal Composite Wick Structure

Authors: I. Brandys, M. Levy, K. Harush, Y. Haim, M. Korngold

Abstract:

Theoretical optimization of a copper-water negative inclination heat pipe with internal composite wick structure had been performed, regarding a new introduced parameter: the ratio between the coarse mesh wraps and the fine mesh wraps of the composite wick. Since in many cases, the design of a heat pipe matches specific thermal requirements and physical limitations, this work demonstrates the optimization of a 1m length, 8mm internal diameter heat pipe without an adiabatic section, at a negative inclination angle of -10º. The optimization is based on a new introduced parameter, LR: the ratio between the coarse mesh wraps and the fine mesh wraps.

Keywords: Heat pipe, inclination, optimization, ratio.

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1036 Fuzzy Controlled Hydraulic Excavator with Model Parameter Uncertainty

Authors: Ganesh Kothapalli, Mohammed Y. Hassan

Abstract:

The hydraulic actuated excavator, being a non-linear mobile machine, encounters many uncertainties. There are uncertainties in the hydraulic system in addition to the uncertain nature of the load. The simulation results obtained in this study show that there is a need for intelligent control of such machines and in particular interval type-2 fuzzy controller is most suitable for minimizing the position error of a typical excavator-s bucket under load variations. We consider the model parameter uncertainties such as hydraulic fluid leakage and friction. These are uncertainties which also depend up on the temperature and alter bulk modulus and viscosity of the hydraulic fluid. Such uncertainties together with the load variations cause chattering of the bucket position. The interval type-2 fuzzy controller effectively eliminates the chattering and manages to control the end-effecter (bucket) position with positional error in the order of few millimeters.

Keywords: excavator, fuzzy control, hydraulics, mining, type-2

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1035 Determination of the Quality of the Machined Surface Using Fuzzy Logic

Authors: Dejan Tanikić, Jelena Đoković, Saša Kalinović, Miodrag Manić, Saša Ranđelović

Abstract:

This paper deals with measuring and modelling of the quality of the machined surface of the metal machining process. The average surface roughness (Ra) which represents the quality of the machined part was measured during the dry turning of the AISI 4140 steel. A large number of factors with the unknown relations among them influences this parameter, and that is why mathematical modelling is extremely complicated. Different values of cutting speed, feed rate, depth of cut (cutting regime) and workpiece hardness causes different surface roughness values. Modelling with soft computing techniques may be very useful in such cases. This paper presents the usage of the fuzzy logic-based system for determining metal machining process parameter in order to find the proper values of cutting regimes.

Keywords: Metal machining, surface roughness, fuzzy logic, process modelling.

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1034 Comparative Analysis of Two Approaches to Joint Signal Detection, ToA and AoA Estimation in Multi-Element Antenna Arrays

Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

Abstract:

In this paper two approaches to joint signal detection, time of arrival (ToA) and angle of arrival (AoA) estimation in multi-element antenna array are investigated. Two scenarios were considered: first one, when the waveform of the useful signal is known a priori and, second one, when the waveform of the desired signal is unknown. For first scenario, the antenna array signal processing based on multi-element matched filtering (MF) with the following non-coherent detection scheme and maximum likelihood (ML) parameter estimation blocks is exploited. For second scenario, the signal processing based on the antenna array elements covariance matrix estimation with the following eigenvector analysis and ML parameter estimation blocks is applied. The performance characteristics of both signal processing schemes are thoroughly investigated and compared for different useful signals and noise parameters.

Keywords: Antenna array, signal detection, ToA, AoA estimation.

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1033 Robust Coherent Noise Suppression by Point Estimation of the Cauchy Location Parameter

Authors: Ephraim Gower, Thato Tsalaile, Monageng Kgwadi, Malcolm Hawksford.

Abstract:

This paper introduces a new point estimation algorithm, with particular focus on coherent noise suppression, given several measurements of the device under test where it is assumed that 1) the noise is first-order stationery and 2) the device under test is linear and time-invariant. The algorithm exploits the robustness of the Pitman estimator of the Cauchy location parameter through the initial scaling of the test signal by a centred Gaussian variable of predetermined variance. It is illustrated through mathematical derivations and simulation results that the proposed algorithm is more accurate and consistently robust to outliers for different tailed density functions than the conventional methods of sample mean (coherent averaging technique) and sample median search.

Keywords: Central limit theorem, Fisher-Cramer Rao, gamma function, Pitman estimator.

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1032 Stable Robust Adaptive Controller and Observer Design for a Class of SISO Nonlinear Systems with Unknown Dead Zone

Authors: Ibrahim F. Jasim

Abstract:

This paper presents a new stable robust adaptive controller and observer design for a class of nonlinear systems that contain i. Coupling of unmeasured states and unknown parameters ii. Unknown dead zone at the system actuator. The system is firstly cast into a modified form in which the observer and parameter estimation become feasible. Then a stable robust adaptive controller, state observer, parameter update laws are derived that would provide global adaptive system stability and desirable performance. To validate the approach, simulation was performed to a single-link mechanical system with a dynamic friction model and unknown dead zone exists at the system actuation. Then a comparison is presented with the results when there is no dead zone at the system actuation.

Keywords: Dead Zone, Nonlinear Systems, Observer, Robust Adaptive Control.

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1031 Using Interval Constrained Petri Nets and Fuzzy Method for Regulation of Quality: The Case of Weight in Tobacco Factory

Authors: Nabli L., Dhouibi H., Collart Dutilleul S., Craye E.

Abstract:

The existence of maximal durations drastically modifies the performance evaluation in Discrete Event Systems (DES). The same particularity may be found on systems where the associated constraints do not concern the time. For example weight measures, in chemical industry, are used in order to control the quantity of consumed raw materials. This parameter also takes a fundamental part in the product quality as the correct transformation process is based upon a given percentage of each essence. Weight regulation therefore increases the global productivity of the system by decreasing the quantity of rejected products. In this paper we present an approach based on mixing different characteristics theories, the fuzzy system and Petri net system to describe the behaviour. An industriel application on a tobacco manufacturing plant, where the critical parameter is the weight is presented as an illustration.

Keywords: Petri Net, Manufacturing systems, Performance evaluation, Fuzzy logic, Tolerant system.

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1030 Parametric Transition as a Spiral Curve and Its Application in Spur Gear Tooth with FEA

Authors: S. H. Yahaya, J. M. Ali, T.A. Abdullah

Abstract:

The exploration of this paper will focus on the Cshaped transition curve. This curve is designed by using the concept of circle to circle where one circle lies inside other. The degree of smoothness employed is curvature continuity. The function used in designing the C-curve is Bézier-like cubic function. This function has a low degree, flexible for the interactive design of curves and surfaces and has a shape parameter. The shape parameter is used to control the C-shape curve. Once the C-shaped curve design is completed, this curve will be applied to design spur gear tooth. After the tooth design procedure is finished, the design will be analyzed by using Finite Element Analysis (FEA). This analysis is used to find out the applicability of the tooth design and the gear material that chosen. In this research, Cast Iron 4.5 % Carbon, ASTM A-48 is selected as a gear material.

Keywords: Bézier-like cubic function, Curvature continuity, Cshapedtransition curve, Spur gear tooth.

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1029 Optimal Criteria for Non-Minimal Phase Plants

Authors: Z. Nemec, R. Matousek

Abstract:

The paper describes the evaluation of quality of control for cases of controlled non-minimal phase plants. Control circuits containing non-minimal phase plants have different properties, they manifest reversed reaction at the beginning of unit step response. For these types of plants are developed special criterion of quality of control, which considers the difference and can be helpful for synthesis of optimal controller tuning. All results are clearly presented using Matlab/Simulink models.

Keywords: control design, non-minimal phase system, optimalcriteria, power plant, heating plant, water turbine, Matlab, Simulink.

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1028 Speed Sensorless Direct Torque Control of a PMSM Drive using Space Vector Modulation Based MRAS and Stator Resistance Estimator

Authors: A. Ameur, B. Mokhtari, N. Essounbouli, L. Mokrani

Abstract:

This paper presents a speed sensorless direct torque control scheme using space vector modulation (DTC-SVM) for permanent magnet synchronous motor (PMSM) drive based a Model Reference Adaptive System (MRAS) algorithm and stator resistance estimator. The MRAS is utilized to estimate speed and stator resistance and compensate the effects of parameter variation on stator resistance, which makes flux and torque estimation more accurate and insensitive to parameter variation. In other hand the use of SVM method reduces the torque ripple while achieving a good dynamic response. Simulation results are presented and show the effectiveness of the proposed method.

Keywords: MRAS, PMSM, SVM, DTC, Speed and Resistance estimation, Sensorless drive

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1027 Use of Linear Programming for Optimal Production in a Production Line in Saudi Food Co.

Authors: Qasim M. Kriri

Abstract:

Few Saudi Arabia production companies face financial profit issues until this moment. This work presents a linear integer programming model that solves a production problem of a Saudi Food Company in Saudi Arabia. An optimal solution to the above-mentioned problem is a Linear Programming solution. In this regard, the main purpose of this project is to maximize profit. Linear Programming Technique has been used to derive the maximum profit from production of natural juice at Saudi Food Co. The operations of production of the company were formulated and optimal results are found out by using Lindo Software that employed Sensitivity Analysis and Parametric linear programming in order develop Linear Programming. In addition, the parameter values are increased, then the values of the objective function will be increased.

Keywords: Parameter linear programming, objective function, sensitivity analysis, optimize profit.

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1026 Harmonic Parameters with HHT and Wavelet Transform for Automatic Sleep Stages Scoring

Authors: Wei-Chih Tang, Shih-Wei Lu, Chih-Mong Tsai, Cheng-Yan Kao, Hsiu-Hui Lee

Abstract:

Previously, harmonic parameters (HPs) have been selected as features extracted from EEG signals for automatic sleep scoring. However, in previous studies, only one HP parameter was used, which were directly extracted from the whole epoch of EEG signal. In this study, two different transformations were applied to extract HPs from EEG signals: Hilbert-Huang transform (HHT) and wavelet transform (WT). EEG signals are decomposed by the two transformations; and features were extracted from different components. Twelve parameters (four sets of HPs) were extracted. Some of the parameters are highly diverse among different stages. Afterward, HPs from two transformations were used to building a rough sleep stages scoring model using the classifier SVM. The performance of this model is about 78% using the features obtained by our proposed extractions. Our results suggest that these features may be useful for automatic sleep stages scoring.

Keywords: EEG, harmonic parameter, Hilbert-Huang transform, sleep stages, wavelet transform.

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1025 Simulation of Voltage Controlled Tunable All Pass Filter Using LM13700 OTA

Authors: Bhaba Priyo Das, Neville Watson, Yonghe Liu

Abstract:

In recent years Operational Transconductance Amplifier based high frequency integrated circuits, filters and systems have been widely investigated. The usefulness of OTAs over conventional OP-Amps in the design of both first order and second order active filters are well documented. This paper discusses some of the tunability issues using the Matlab/Simulink® software which are previously unreported for any commercial OTA. Using the simulation results two first order voltage controlled all pass filters with phase tuning capability are proposed.

Keywords: All pass filter, Operational Transconductance Amplifier, Simulation.

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1024 A 4-Element Corporate Series Feed Millimeter-Wave Microstrip Antenna Array for 5G Applications

Authors: G. Viswanadh Raviteja

Abstract:

In this paper, a microstrip antenna array is designed for 5G applications. A corporate series feed is considered to operate with a center frequency between 27 to 28 GHz to be able to cover the 5G frequency bands 24.25-27.5 GHz, 26.5-29.5 GHz and 27.5-28.35 GHz. The substrate is taken to be Rogers RT/Duroid 6002. The corporate series 5G antenna array is designed stage by stage by taking into consideration a conventional antenna designed at 28 GHz, thereby constructing the 2X1 antenna array before arriving at the final design structure of 4-element corporate series feed antenna array. The discussions concerning S11 parameter, gain and voltage standing wave ratio (VSWR) for the design structures are considered and all the important findings are tabulated. The proposed antenna array’s S11 parameter was found to be -29.00 dB at a frequency of 27.39 GHz with a good directional gain of 12.12 dB.

Keywords: Corporate series feed, millimeter wave antenna array, 5G applications, millimeter-wave (mm-wave) applications

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1023 Performance Analysis of the First-Order Characteristics of Polling Systems Based on Parallel Limited (k = 1) Services Mode

Authors: Liu Yi, Bao Liyong

Abstract:

Aiming at the problem of low efficiency of pipelined scheduling in periodic query-qualified service, this paper proposes a system service resource scheduling strategy with parallel optimized qualified service polling control. The paper constructs the polling queuing system and its mathematical model; firstly, the first-order and second-order characteristic parameter equations are obtained by partial derivation of the probability mother function of the system state variables, and the complete mathematical, analytical expressions of each system parameter are deduced after the joint solution. The simulation experimental results are consistent with the theoretical calculated values. The system performance analysis shows that the average captain and average period of the system have been greatly improved, which can better adapt to the service demand of delay-sensitive data in the dense data environment.

Keywords: Polling, parallel scheduling, mean queue length, average cycle time.

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1022 The Influence of Preprocessing Parameters on Text Categorization

Authors: Jan Pomikalek, Radim Rehurek

Abstract:

Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.

Keywords: Text categorization, machine learning, electronic documents, classification.

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1021 Revolving Ferrofluid Flow in Porous Medium with Rotating Disk

Authors: Paras Ram, Vikas Kumar

Abstract:

An attempt has been made to study the effect of rotation on incompressible, electrically non-conducting ferrofluid in porous medium on Axi-symmetric steady flow over a rotating disk excluding thermal effects. Here, we solved the boundary layer equations with boundary conditions using Neuringer-Rosensweig model considering the z-axis as the axis of rotation. The non linear boundary layer equations involved in the problem are transformed to the non linear coupled ordinary differential equations by Karman's transformation and solved by power series approximations. Besides numerically calculating the velocity components and pressure for different values of porosity parameter with the variation of Karman's parameter we have also calculated the displacement thickness of boundary layer, the total volume flowing outward the z-axis and angle between wall and ferrofluid. The results for all above variables are obtained numerically and discussed graphically.

Keywords: Ferrofluid, magnetic field porous medium, rotating disk.

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1020 Design and Implementation of a Hybrid Fuzzy Controller for a High-Performance Induction

Authors: M. Zerikat, S. Chekroun

Abstract:

This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variations and external influences. Some fundamentals of the fuzzy logic control are preliminary illustrated. The developed control algorithm is robust, efficient and simple. It also assures precise trajectory tracking with the prescribed dynamics. Experimental results have shown excellent tracking performance of the proposed control system, and have convincingly demonstrated the validity and the usefulness of the hybrid fuzzy controller in high-performance drives with parameter and load uncertainties. Satisfactory performance was observed for most reference tracks.

Keywords: Fuzzy controller, high-performance, inductionmotor, intelligent control, robustness.

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1019 Simulating Discrete Time Model Reference Adaptive Control System with Great Initial Error

Authors: Bubaker M. F. Bushofa, Abdel Hafez A. Azab

Abstract:

This article is based on the technique which is called Discrete Parameter Tracking (DPT). First introduced by A. A. Azab [8] which is applicable for less order reference model. The order of the reference model is (n-l) and n is the number of the adjustable parameters in the physical plant. The technique utilizes a modified gradient method [9] where the knowledge of the exact order of the nonadaptive system is not required, so, as to eliminate the identification problem. The applicability of the mentioned technique (DPT) was examined through the solution of several problems. This article introduces the solution of a third order system with three adjustable parameters, controlled according to second order reference model. The adjustable parameters have great initial error which represent condition. Computer simulations for the solution and analysis are provided to demonstrate the simplicity and feasibility of the technique.

Keywords: Adaptive Control System, Discrete Parameter Tracking, Discrete Time Model.

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1018 Determination of the Best Fit Probability Distribution for Annual Rainfall in Karkheh River at Iran

Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best-fit probability distribution of annual rainfall based on 50 years sample (1966-2015) in the Karkheh river basin at Iran using six probability distributions: Normal, 2-Parameter Log Normal, 3-Parameter Log Normal, Pearson Type 3, Log Pearson Type 3 and Gumbel distribution. The best fit probability distribution was selected using Stormwater Management and Design Aid (SMADA) software and based on the Residual Sum of Squares (R.S.S) between observed and estimated values Based on the R.S.S values of fit tests, the Log Pearson Type 3 and then Pearson Type 3 distributions were found to be the best-fit probability distribution at the Jelogir Majin and Pole Zal rainfall gauging station. The annual values of expected rainfall were calculated using the best fit probability distributions and can be used by hydrologists and design engineers in future research at studied region and other region in the world.

Keywords: Log Pearson Type 3, SMADA, rainfall, Karkheh River.

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1017 Further Thoughtson a Sequential Life Testing Approach Using an Inverse Weibull Model

Authors: D. I. De Souza, G. P. Azevedo, D. R. Fonseca

Abstract:

In this paper we will develop further the sequential life test approach presented in a previous article by [1] using an underlying two parameter Inverse Weibull sampling distribution. The location parameter or minimum life will be considered equal to zero. Once again we will provide rules for making one of the three possible decisions as each observation becomes available; that is: accept the null hypothesis H0; reject the null hypothesis H0; or obtain additional information by making another observation. The product being analyzed is a new electronic component. There is little information available about the possible values the parameters of the corresponding Inverse Weibull underlying sampling distribution could have.To estimate the shape and the scale parameters of the underlying Inverse Weibull model we will use a maximum likelihood approach for censored failure data. A new example will further develop the proposed sequential life testing approach.

Keywords: Sequential Life Testing, Inverse Weibull Model, Maximum Likelihood Approach, Hypothesis Testing.

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1016 Investigations on the Influence of Process Parameters on the Sliding Wear Behavior of Components Produced by Direct Metal Laser Sintering (DMLS)

Authors: C. D. Naiju, K. Annamalai, Siva Prasad Darla, Y. Murali Krishna

Abstract:

This work presents the results of a study carried out to determine the sliding wear behavior and its effect on the process parameters of components manufactured by direct metal laser sintering (DMLS). A standard procedure and specimen had been used in the present study to find the wear behavior. Using Taguchi-s experimental technique, an orthogonal array of modified L8 had been developed. Sliding wear testing using pin-on-disk machine was carried out and analysis of variance (ANOVA) technique was used to investigate the effect of process parameters and to identify the main process parameter that influences the properties of wear behavior on the DMLS components. It has been found that part orientation, one of the selected process parameter had more influence on wear as compared to other selected process parameters.

Keywords: ANOVA, DMLS, Taguchi, Wear.

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1015 Optimization of Loudspeaker Part Design Parameters by Air Viscosity Damping Effect

Authors: Yue Hu, Xilu Zhao, Takao Yamaguchi, Manabu Sasajima, Yoshio Koike, Akira Hara

Abstract:

This study optimized the design parameters of a cone loudspeaker as an example of high flexibility of the product design. We developed an acoustic analysis software program that considers the impact of damping caused by air viscosity. In sound reproduction, it is difficult to optimize each parameter of the loudspeaker design. To overcome the limitation of the design problem in practice, this study presents an acoustic analysis algorithm to optimize the design parameters of the loudspeaker. The material character of cone paper and the loudspeaker edge were the design parameters, and the vibration displacement of the cone paper was the objective function. The results of the analysis showed that the design had high accuracy as compared to the predicted value. These results suggested that although the parameter design is difficult, with experience and intuition, the design can be performed easily using the optimized design found with the acoustic analysis software.

Keywords: Air viscosity, design parameters, loudspeaker, optimization.

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1014 Lagrange-s Inversion Theorem and Infiltration

Authors: Pushpa N. Rathie, Prabhata K. Swamee, André L. B. Cavalcante, Luan Carlos de S. M. Ozelim

Abstract:

Implicit equations play a crucial role in Engineering. Based on this importance, several techniques have been applied to solve this particular class of equations. When it comes to practical applications, in general, iterative procedures are taken into account. On the other hand, with the improvement of computers, other numerical methods have been developed to provide a more straightforward methodology of solution. Analytical exact approaches seem to have been continuously neglected due to the difficulty inherent in their application; notwithstanding, they are indispensable to validate numerical routines. Lagrange-s Inversion Theorem is a simple mathematical tool which has proved to be widely applicable to engineering problems. In short, it provides the solution to implicit equations by means of an infinite series. To show the validity of this method, the tree-parameter infiltration equation is, for the first time, analytically and exactly solved. After manipulating these series, closed-form solutions are presented as H-functions.

Keywords: Green-Ampt Equation, Lagrange's Inversion Theorem, Talsma-Parlange Equation, Three-Parameter Infiltration Equation

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1013 Synthesis of a Control System of a Deterministic Chaotic Process in the Class of Two-Parameter Structurally Stable Mappings

Authors: M. Beisenbi, A. Sagymbay, S. Beisembina, A. Satpayeva

Abstract:

In this paper, the problem of unstable and deterministic chaotic processes in control systems is considered. The synthesis of a control system in the class of two-parameter structurally stable mappings is demonstrated. This is realized via the gradient-velocity method of Lyapunov vector functions. It is shown that the gradient-velocity method of Lyapunov vector functions allows generating an aperiodic robust stable system with the desired characteristics. A simple solution to the problem of synthesis of control systems for unstable and deterministic chaotic processes is obtained. Moreover, it is applicable for complex systems.

Keywords: Control system synthesis, deterministic chaotic processes, Lyapunov vector function, robust stability, structurally stable mappings.

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1012 Comparison of Evolutionary Algorithms and their Hybrids Applied to MarioAI

Authors: Hidehiko Okada, Yuki Fujii

Abstract:

Researchers have been applying artificial/ computational intelligence (AI/CI) methods to computer games. In this research field, further researchesare required to compare AI/CI methods with respect to each game application. In thispaper, we report our experimental result on the comparison of evolution strategy, genetic algorithm and their hybrids, applied to evolving controller agents for MarioAI. GA revealed its advantage in our experiment, whereas the expected ability of ES in exploiting (fine-tuning) solutions was not clearly observed. The blend crossover operator and the mutation operator of GA might contribute well to explore the vast search space.

Keywords: Evolutionary algorithm, autonomous game controller agent, neuroevolutions, MarioAI

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1011 Confidence Intervals for the Coefficients of Variation with Bounded Parameters

Authors: Jeerapa Sappakitkamjorn, Sa-aat Niwitpong

Abstract:

In many practical applications in various areas, such as engineering, science and social science, it is known that there exist bounds on the values of unknown parameters. For example, values of some measurements for controlling machines in an industrial process, weight or height of subjects, blood pressures of patients and retirement ages of public servants. When interval estimation is considered in a situation where the parameter to be estimated is bounded, it has been argued that the classical Neyman procedure for setting confidence intervals is unsatisfactory. This is due to the fact that the information regarding the restriction is simply ignored. It is, therefore, of significant interest to construct confidence intervals for the parameters that include the additional information on parameter values being bounded to enhance the accuracy of the interval estimation. Therefore in this paper, we propose a new confidence interval for the coefficient of variance where the population mean and standard deviation are bounded. The proposed interval is evaluated in terms of coverage probability and expected length via Monte Carlo simulation.  

Keywords: Bounded parameters, coefficient of variation, confidence interval, Monte Carlo simulation.

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1010 Design of Identification Based Adaptive Control for Fermentation Process in Bioreactor

Authors: J. Ritonja

Abstract:

The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: Adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification.

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