Search results for: Hybrid Fuzzy Selecting

Authors: Xu Guoliang, Tan Qingping

Abstract:

Color printing proceeds with multiple halftone separations overlay. Because of separation overlay misalignment in printing, the percentage of different primary color combination may vary and it will result in color shift. In traditional printing procedure with AM halftone, every separation has different screening angle to make the superposition pattern in a random style, which will reduce the color shift. To evaluate the color shift of printing with hybrid halftoning, we simulate printing procedure with halftone images overlay and calculate the color difference between expected color and color in different overlay misalignment configurations. The color difference for hybrid halftone and AM halftone is very close. So the color shift for hybrid halftone is acceptable with current color printing procedure.

Keywords: color printing, AM halftone, Hybrid halftone, misalignment, color shift, Neugebauer Color Equation

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Authors: Debajyoti Mishra, Urmila Bhanja

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In this paper, a novel fuzzy approach is developed while solving the Dynamic Routing and Wavelength Assignment (DRWA) problem in optical networks with Wavelength Division Multiplexing (WDM). In this work, the effect of nonlinear and linear impairments such as Four Wave Mixing (FWM) and amplifier spontaneous emission (ASE) noise are incorporated respectively. The novel algorithm incorporates fuzzy logic controller (FLC) to reduce the effect of FWM noise and ASE noise on a requested lightpath referred in this work as FWM aware fuzzy dynamic routing and wavelength assignment algorithm. The FWM crosstalk products and the static FWM noise power per link are pre computed in order to reduce the set up time of a requested lightpath, and stored in an offline database. These are retrieved during the setting up of a lightpath and evaluated online taking the dynamic parameters like cost of the links into consideration.

Keywords: Amplifier spontaneous emission (ASE), Dynamic routing and wavelength assignment, Four wave mixing (FWM), Fuzzy rule based system (FRBS).

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Authors: Sushovan Sarkar, Debabrata Mazumder

Abstract:

Hybrid bioreactor having both suspended-growth and attached-growth bacteria is found a novel and excellent bioreactor system for treating the municipal wastewater containing inhibitory substrates too. In this reactor a fraction of substrate is used by suspended biomass and the remaining by attached biomass resulting in the competition between the two growths for the substrate. The combination of suspended and attached growth provides the system with enhanced biomass concentration and sludge age more than those in ASP. Similar to attached growth system, the hybrid bioreactor ensures considerable efficiency for treating toxic and refractory substances in wastewater. For the process design of hybrid bioreactor a suitable mathematical model is required. Although various mathematical models were developed on hybrid bioreactor in due course of time in earlier research works, none of them was found having a specific simplified solution of the corresponding models and without having any drawback. To overcome this drawback authors already developed a simplified mathematical model for process design of a hybrid bioreactor. The present paper briefly highlights on the various aspects of process design of an aerobic hybrid bioreactor for the treatment of municipal wastewater.

Keywords: Hybrid bioreactor, mathematical model, process design, application, municipal wastewater.

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Authors: Sri Hartati, 1Agus Harjoko, Brad G. Nickerson

Abstract:

A prototype of an anomaly detection system was developed to automate process of recognizing an anomaly of roentgen image by utilizing fuzzy histogram hyperbolization image enhancement and back propagation artificial neural network. The system consists of image acquisition, pre-processor, feature extractor, response selector and output. Fuzzy Histogram Hyperbolization is chosen to improve the quality of the roentgen image. The fuzzy histogram hyperbolization steps consist of fuzzyfication, modification of values of membership functions and defuzzyfication. Image features are extracted after the the quality of the image is improved. The extracted image features are input to the artificial neural network for detecting anomaly. The number of nodes in the proposed ANN layers was made small. Experimental results indicate that the fuzzy histogram hyperbolization method can be used to improve the quality of the image. The system is capable to detect the anomaly in the roentgen image.

Keywords: Image processing, artificial neural network, anomaly detection.

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Authors: Lazim Abdullah, N orhanadiah Zam

Abstract:

Increasing number of vehicles and lack of awareness among road users may lead to road accidents. However no specific literature was found to rank vehicles involved in accidents based on fuzzy variables of road users. This paper proposes a ranking of four selected motor vehicles involved in road accidents. Human and non-human factors that normally linked with road accidents are considered for ranking. The imprecision or vagueness inherent in the subjective assessment of the experts has led the application of fuzzy sets theory to deal with ranking problems. Data in form of linguistic variables were collected from three authorised personnel of three Malaysian Government agencies. The Multi Criteria Decision Making, fuzzy TOPSIS was applied in computational procedures. From the analysis, it shows that motorcycles vehicles yielded the highest closeness coefficient at 0.6225. A ranking can be drawn using the magnitude of closeness coefficient. It was indicated that the motorcycles recorded the first rank.

Keywords: Road accidents, decision making, closeness coefficient, fuzzy number

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Authors: Ayman A. Aly, Abdallah A. Alshnnaway

Abstract:

The general idea behind the filter is to average a pixel using other pixel values from its neighborhood, but simultaneously to take care of important image structures such as edges. The main concern of the proposed filter is to distinguish between any variations of the captured digital image due to noise and due to image structure. The edges give the image the appearance depth and sharpness. A loss of edges makes the image appear blurred or unfocused. However, noise smoothing and edge enhancement are traditionally conflicting tasks. Since most noise filtering behaves like a low pass filter, the blurring of edges and loss of detail seems a natural consequence. Techniques to remedy this inherent conflict often encompass generation of new noise due to enhancement. In this work a new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of three stages. (1) Define fuzzy sets in the input space to computes a fuzzy derivative for eight different directions (2) construct a set of IFTHEN rules by to perform fuzzy smoothing according to contributions of neighboring pixel values and (3) define fuzzy sets in the output space to get the filtered and edged image. Experimental results are obtained to show the feasibility of the proposed approach with two dimensional objects.

Keywords: Additive noise, edge preserving filtering, fuzzy image filtering, noise reduction, two dimensional mechanical images.

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Authors: Rishabh Sharma, Renu Vig, Neeraj Sharma

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The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: Wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system.

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Authors: Xinhua Zhang, Kelin Li

Abstract:

In this paper, the problem of stability analysis for a class of impulsive stochastic fuzzy neural networks with timevarying delays and reaction-diffusion is considered. By utilizing suitable Lyapunov-Krasovskii funcational, the inequality technique and stochastic analysis technique, some sufficient conditions ensuring global exponential stability of equilibrium point for impulsive stochastic fuzzy cellular neural networks with time-varying delays and diffusion are obtained. In particular, the estimate of the exponential convergence rate is also provided, which depends on system parameters, diffusion effect and impulsive disturbed intention. It is believed that these results are significant and useful for the design and applications of fuzzy neural networks. An example is given to show the effectiveness of the obtained results.

Keywords: Exponential stability, stochastic fuzzy cellular neural networks, time-varying delays, impulses, reaction-diffusion terms.

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Authors: E. Farshidi

Abstract:

In this paper, based on a novel synthesis, a set of new simplified circuit design to implement the linguistic-hedge operations for adjusting the fuzzy membership function set is presented. The circuits work in current-mode and employ floating-gate MOS (FGMOS) transistors that operate in weak inversion region. Compared to the other proposed circuits, these circuits feature severe reduction of the elements number, low supply voltage (0.7V), low power consumption (<200nW), immunity from body effect and wide input dynamic range (>60dB). In this paper, a set of fuzzy linguistic hedge circuits, including absolutely, very, much more, more, plus minus, more or less and slightly, has been implemented in 0.18 mm CMOS process. Simulation results by Hspice confirm the validity of the proposed design technique and show high performance of the circuits.

Keywords: Current-mode, Linguistic-Hedge, Fuzzy Logic, lowpower

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Authors: Tae Kyung Kim, Hee Suk Seo

Abstract:

Adapting various sensor devices to communicate within sensor networks empowers us by providing range of possibilities. The sensors in sensor networks need to know their measurable belief of trust for efficient and safe communication. In this paper, we suggested a trust model using fuzzy logic in sensor network. Trust is an aggregation of consensus given a set of past interaction among sensors. We applied our suggested model to sensor networks in order to show how trust mechanisms are involved in communicating algorithm to choose the proper path from source to destination.

Keywords: Fuzzy, Sensor Networks, Trust.

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Authors: Preeda Sansakorn, Min An

Abstract:

In order to be capable of dealing with uncertainties, subjectivities, including vagueness arising in building construction projects, the application of fuzzy reasoning technique based on fuzzy set theory is proposed. This study contributes significantly to the development of a fuzzy reasoning safety risk assessment model for building construction projects that could be employed to assess the risk magnitude of each hazardous event identified during construction, and a third parameter of probability of consequence is incorporated in the model. By using the proposed safety risk analysis methodology, more reliable and less ambiguities, which provide the safety risk management project team for decision-making purposes.

Keywords: Safety risks assessment, building construction safety, fuzzy reasoning, construction risk assessment model, building construction projects.

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Authors: Hae Young Lee, Tae Ho Cho

Abstract:

In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false reports during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and overhead. In this paper, we propose a fuzzy logic for determining a security threshold value in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the number of partitions in a global key pool, the number of compromised partitions, and the energy level of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.

Keywords: Fuzzy logic, security, sensor network.

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Authors: Richard A. Wasniowski

Abstract:

In this paper we propose a framework for multisensor intrusion detection called Fuzzy Agent-Based Intrusion Detection System. A unique feature of this model is that the agent uses data from multiple sensors and the fuzzy logic to process log files. Use of this feature reduces the overhead in a distributed intrusion detection system. We have developed an agent communication architecture that provides a prototype implementation. This paper discusses also the issues of combining intelligent agent technology with the intrusion detection domain.

Keywords: Intrusion detection, fuzzy logic, agents, networksecurity.

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Authors: Bing Lu, Shuang Li, Hongyuan Zhou

Abstract:

The steel-concrete hybrid structure has been extensively employed in high-rise buildings and super high-rise buildings. The light gauge steel-concrete hybrid structure, including light gauge steel structure and concrete hybrid structure, is a type of steel-concrete hybrid structure, which possesses some advantages of light gauge steel structure and concrete hybrid structure. The seismic behavior and loss assessment of three high-rise buildings with three different concrete hybrid structures were investigated through finite element software. The three concrete hybrid structures are reinforced concrete column-steel beam (RC-S) hybrid structure, concrete-filled steel tube column-steel beam (CFST-S) hybrid structure, and tubed concrete column-steel beam (TC-S) hybrid structure. The nonlinear time-history analysis of three high-rise buildings under 80 earthquakes was carried out. After simulation, it indicated that the seismic performances of three high-rise buildings were superior. Under extremely rare earthquakes, the maximum inter-story drifts of three high-rise buildings are significantly lower than 1/50. The inter-story drift and floor acceleration of high-rise building with CFST-S hybrid structure were bigger than those of high-rise buildings with RC-S hybrid structure, and smaller than those of high-rise building with TC-S hybrid structure. Then, based on the time-history analysis results, the post-earthquake repair cost ratio and repair time of three high-rise buildings were predicted through an economic performance analysis method proposed in FEMA-P58 report. Under frequent earthquakes, basic earthquakes and rare earthquakes, the repair cost ratio and repair time of three high-rise buildings were less than 5% and 15 days, respectively. Under extremely rare earthquakes, the repair cost ratio and repair time of high-rise buildings with TC-S hybrid structure were the most among three high rise buildings. Due to the advantages of CFST-S hybrid structure, it could be extensively employed in high-rise buildings subjected to earthquake excitations.

Keywords: seismic behavior, loss assessment, light gauge steel, concrete hybrid structure, high-rise building, time-history analysis

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Authors: N. Kumaresan, J. Kavikumar, M. Kumudthaa, Kuru Ratnavelu

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In this paper, solution of fuzzy differential equation under general differentiability is obtained by genetic programming (GP). The obtained solution in this method is equivalent or very close to the exact solution of the problem. Accuracy of the solution to this problem is qualitatively better. An illustrative numerical example is presented for the proposed method.

Keywords: Fuzzy differential equation, Generalized differentiability, Genetic programming and H-difference.

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Authors: Oshmita Dey, Debjani Chakraborty

Abstract:

In this paper, a single period inventory model with resalable returns has been analyzed in an imprecise and uncertain mixed environment. Demand has been introduced as a fuzzy random variable. In this model, a single order is placed before the start of the selling season. The customer, for a full refund, may return purchased products within a certain time interval. Returned products are resalable, provided they arrive back before the end of the selling season and are found to be undamaged. Products remaining at the end of the season are salvaged. All demands not met directly are lost. The probabilities that a sold product is returned and that a returned product is resalable, both imprecise in a real situation, have been assumed to be fuzzy in nature.

Keywords: Fuzzy random variable, Modified graded meanintegration, Internet mail order, Inventory.

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Authors: Swathi Sampath, V. Kalaichelvi

Abstract:

The assessment of the risk posed by a borrower to a lender is one of the common problems that financial institutions have to deal with. Consumers vying for a mortgage are generally compared to each other by the use of a number called the Credit Score, which is generated by applying a mathematical algorithm to information in the applicant’s credit report. The higher the credit score, the lower the risk posed by the candidate, and the better he is to be taken on by the lender. The objective of the present work is to use fuzzy logic and linguistic rules to create a model that generates Credit Scores.

Keywords: Credit scoring, fuzzy logic, mortgage, risk assessment.

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Authors: Jianhua Wang, Yan Yu

Abstract:

This paper presents an intrusion detection system of hybrid neural network model based on RBF and Elman. It is used for anomaly detection and misuse detection. This model has the memory function .It can detect discrete and related aggressive behavior effectively. RBF network is a real-time pattern classifier, and Elman network achieves the memory ability for former event. Based on the hybrid model intrusion detection system uses DARPA data set to do test evaluation. It uses ROC curve to display the test result intuitively. After the experiment it proves this hybrid model intrusion detection system can effectively improve the detection rate, and reduce the rate of false alarm and fail.

Keywords: RBF, Elman, anomaly detection, misuse detection, hybrid neural network.

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Authors: Eleftherios Giovanis

Abstract:

In this paper discrete choice models, Logit and Probit are examined in order to predict the economic recession or expansion periods in USA. Additionally we propose an adaptive neuro-fuzzy inference system with triangular membership function. We examine the in-sample period 1947-2005 and we test the models in the out-of sample period 2006-2009. The forecasting results indicate that the Adaptive Neuro-fuzzy Inference System (ANFIS) model outperforms significant the Logit and Probit models in the out-of sample period. This indicates that neuro-fuzzy model provides a better and more reliable signal on whether or not a financial crisis will take place.

Keywords: ANFIS, discrete choice models, financial crisis, USeconomy

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Authors: Nastaran Hajiheydari, Mohammad Soltani Delgosha

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Vendor (supplier) selection is a group decision-making (GDM) process, in which, based on some predetermined criteria, the experts’ preferences are provided in order to rank and choose the most desirable suppliers. In the real business environment, our attitudes or our choices would be made in an uncertain and indecisive situation could not be expressed in a crisp framework. Intuitionistic fuzzy sets (IFSs) could handle such situations in the best way. VIKOR method was developed to solve multi-criteria decision-making (MCDM) problems. This method, which is used to determine the compromised feasible solution with respect to the conflicting criteria, introduces a multi-criteria ranking index based on the particular measure of 'closeness' to the 'ideal solution'. Until now, there has been a little investigation of VIKOR with IFS, therefore we extended the intuitionistic fuzzy (IF) VIKOR to solve vendor selection problem under IF GDM environment. The present study intends to develop an IF VIKOR method in a GDM situation. Therefore, a model is presented to calculate the criterion weights based on entropy measure. Then, the interval-valued intuitionistic fuzzy weighted geometric (IFWG) operator utilized to obtain the total decision matrix. In the next stage, an approach based on the positive idle intuitionistic fuzzy number (PIIFN) and negative idle intuitionistic fuzzy number (NIIFN) was developed. Finally, the application of the proposed method to solve a vendor selection problem illustrated.

Keywords: Group decision making, intuitionistic fuzzy entropy measure, intuitionistic fuzzy set, vendor selection VIKOR.

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Authors: A. Hasankhani, H. Saadat, M. M. Zahedi

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In this paper some properties of the uniformity topology on a BCI-algebras are discussed.

Keywords: (Fuzzy) ideal, (Fuzzy) subalgebra, Uniformity, clopen sets.

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Authors: Saeed Safari Dolatabad, Rajab Choukan

Abstract:

Selection of maize (Zea mays) hybrids with wide adaptability across diverse farming environments is important, prior to recommending them to achieve a high rate of hybrid adoption. Grain yield of 14 maize hybrids, tested in a randomized completeblock design with four replicates across 22 environments in Iran, was analyzed using site regression (SREG) stability model. The biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and mega-environment identification. The objectives of this study were (i) identification of suitable hybrids with both high mean performance and high stability (ii) to determine mega-environments for maize production in Iran. Biplot analysis identifies two mega-environments in this study. The first mega-environments included KRM, KSH, MGN, DZF A, KRJ, DRB, DZF B, SHZ B, and KHM, where G10 hybrid was the best performing hybrid. The second mega-environment included ESF B, ESF A, and SHZ A, where G4 hybrid was the best hybrid. According to the ideal-hybrid biplot, G10 hybrid was better than all other hybrids, followed by the G1 and G3 hybrids. These hybrids were identified as best hybrids that have high grain yield and high yield stability. GGE biplot analysis provided a framework for identifying the target testing locations that discriminates genotypes that are high yielding and stable.

Keywords: Zea mays L, GGE biplot, Multi-environment trials, Yield stability.

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Authors: M.Saleem Khan, Khaled Benkrid

Abstract:

This paper presents a time control liquids mixing system in the tanks as an application of fuzzy time control discrete model. The system is designed for a wide range of industrial applications. The simulation design of control system has three inputs: volume, viscosity, and selection of product, along with the three external control adjustments for the system calibration or to take over the control of the system autonomously in local or distributed environment. There are four controlling elements: rotatory motor, grinding motor, heating and cooling units, and valves selection, each with time frame limit. The system consists of three controlled variables measurement through its sensing mechanism for feed back control. This design also facilitates the liquids mixing system to grind certain materials in tanks and mix with fluids under required temperature controlled environment to achieve certain viscous level. Design of: fuzzifier, inference engine, rule base, deffuzifiers, and discrete event control system, is discussed. Time control fuzzy rules are formulated, applied and tested using MATLAB simulation for the system.

Keywords: Fuzzy time control, industrial application and timecontrol systems, adjustment of Fuzzy system, liquids mixing system, design of fuzzy time control DEV system.

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Authors: Z. Abdollahnejad, M. Mastali, F. Pacheco-Torgal

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Waste reuse is crucial in a context of circular economy and zero waste sustainable needs. Some wastes deserve further studies by the scientific community not only because they are generated in high amount but also because they have a low reuse rate. This paper reports results of 32 hybrid cement mortars based on fly ash and waste glass. They allow to explore the influence of mix design on the cost and on the embodied carbon of the hybrid cement mortars. The embodied carbon data for all constituents were taken from the database Ecoinvent. This study led to the development of a mixture with just 70 kg CO2e.

Keywords: Waste reuse, fly ash, waste glass, hybrid cements, cost, embodied carbon.

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Authors: Mahmoud Saeidi, Khadijeh Saeidi, Mahmoud Khaleghi

Abstract:

In this paper, we propose a novel spatiotemporal fuzzy based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership functions. In this algorithm median filter is used to suppress noise. Experimental results show when the images are corrupted by highdensity Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.

Keywords: Image Sequences, Noise Reduction, fuzzy algorithm, triangular membership function

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Authors: Alexandre Boum, Salomon Madinatou

Abstract:

This paper aims at bringing a scientific contribution to the cardiac arrhythmia biomedical diagnosis systems; more precisely to the study of the amelioration of cardiac arrhythmia classification performance using artificial neural network, adaptive neuro-fuzzy and fuzzy inference systems classifiers. The purpose of this amelioration is to enable cardiologists to make reliable diagnosis through automatic cardiac arrhythmia analyzes and classifications based on high confidence classifiers. In this study, six classes of the most commonly encountered arrhythmias are considered: the Right Bundle Branch Block, the Left Bundle Branch Block, the Ventricular Extrasystole, the Auricular Extrasystole, the Atrial Fibrillation and the Normal Cardiac rate beat. From the electrocardiogram (ECG) extracted parameters, we constructed a matrix (360x360) serving as an input data sample for the classifiers based on neural networks and a matrix (1x6) for the classifier based on fuzzy logic. By varying three parameters (the quality of the neural network learning, the data size and the quality of the input parameters) the automatic classification permitted us to obtain the following performances: in terms of correct classification rate, 83.6% was obtained using the fuzzy logic based classifier, 99.7% using the neural network based classifier and 99.8% for the adaptive neuro-fuzzy based classifier. These results are based on signals containing at least 360 cardiac cycles. Based on the comparative analysis of the aforementioned three arrhythmia classifiers, the classifiers based on neural networks exhibit a better performance.

Keywords: Adaptive neuro-fuzzy, artificial neural network, cardiac arrythmias, fuzzy inference systems.

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Authors: Abolfazl Jalilvand, Mohammad Reza Feyzi, Sohrab Khanmohammad, Mohammad Bagher Bana Sharifian, Ali Sajjadi

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Nowadays the control of stator voltage at a constant frequency is one of the traditional and low expense methods in order to control the speed of induction motors near its nominal speed. The torque of induction motor is a nonlinear function of the firing angle, phase angle and speed. In this paper the speed control of induction motor regarding various load torque and under different conditions will be investigated based on a fuzzy controller with inverse training.

Keywords: Three phase induction motor, AC converter, speedcontrol, fuzzy control.

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Authors: M. Rahmah, Noor Zuhaira Abd Aziz, M. Mohd Muizz Fahimi, M. Farhan

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Poly bag and mulch films for agricultural field caused pose environmental problem due to the non-degradable plastics wastes upon disposal. Thus, a degradable poly bag was designed with hybrid sago starch (SS) and polyvinyl alcohol (PVA). Two Different blended compositions of SS and PVA hybrid have been compounded. Then, the hybrids blended are mixed with linear line density polyethylene (LLDPE) resin to fabricate poly bag film through conventional film blowing process. Samples of LLDPE, SS and PVA hybrid film were exposed to UV light and soil burial. The weight losses were determined during degradation process. Hybrid film by degradation of starch was found to hydrolyze and hydroxyl groups decrease on esterification upon exposure to soil burial and uv radiation. It was found out that, the hybrid film for 60% of SS composition showed greatest degradation in soil and UV radiation.

Keywords: LLDPE, PVA, sago starch, degradation, soil burial, UV radiation.

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Authors: Ali Fellah Jahromi, Wen Fang Xie, Rama B. Bhat

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A semi-active control strategy for suspension systems of passenger cars is presented employing Magnetorheological (MR) dampers. The vehicle is modeled with seven DOFs including the, roll pitch and bounce of car body, and the vertical motion of the four tires. In order to design an optimal controller based on the actuator constraints, a Linear-Quadratic Regulator (LQR) is designed. The design procedure of the LQR consists of selecting two weighting matrices to minimize the energy of the control system. This paper presents a hybrid optimization procedure which is a combination of gradient-based and evolutionary algorithms to choose the weighting matrices with regards to the actuator constraint. The optimization algorithm is defined based on maximum comfort and actuator constraints. It is noted that utilizing the present control algorithm may significantly reduce the vibration response of the passenger car, thus, providing a comfortable ride.

Keywords: Full car model, Linear Quadratic Regulator, Sequential Quadratic Programming, Genetic Algorithm

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Authors: Seungwoo Kim, Hyojune Chae, Yongrae Jung, Jongwook Kim

Abstract:

Recent medical studies have investigated the importance of enteral feeding and the use of feeding pumps for recovering patients unable to feed themselves or gain nourishment and nutrients by natural means. The most of enteral feeding system uses a peristaltic tube pump. A peristaltic pump is a form of positive displacement pump in which a flexible tube is progressively squeezed externally to allow the resulting enclosed pillow of fluid to progress along it. The squeezing of the tube requires a precise and robust controller of the geared motor to overcome parametric uncertainty of the pumping system which generates due to a wide variation of friction and slip between tube and roller. So, this paper proposes fuzzy adaptive controller for the robust control of the peristaltic tube pump. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good control performance, accurate dose rate and robust system stability, of the developed feeding pump is confirmed through experimental and clinic testing.

Keywords: Enteral Feeding Pump, Peristaltic Tube Pump, Fuzzy Adaptive Control, Fuzzy Multi-layered Controller, Look-up Table..

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