Search results for: intelligent controller and two wheel inverted pendulum.

Authors: A. Puras Trueba, J. R. Llata García

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A nonlinear optimal controller with a fuzzy gain scheduler has been designed and applied to a Line-Of-Sight (LOS) stabilization system. Use of Linear Quadratic Regulator (LQR) theory is an optimal and simple manner of solving many control engineering problems. However, this method cannot be utilized directly for multigimbal LOS systems since they are nonlinear in nature. To adapt LQ controllers to nonlinear systems at least a linearization of the model plant is required. When the linearized model is only valid within the vicinity of an operating point a gain scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference System gain scheduler has been implemented, which keeps the asymptotic stability performance provided by the optimal feedback gain approach. The simulation results illustrate that the proposed controller is capable of overcoming disturbances and maintaining a satisfactory tracking performance.

Keywords: Fuzzy Gain-Scheduling, Gimbal, Line-Of-SightStabilization, LQR, Optimal Control

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Authors: T. Sopapirm, K-N. Areerak, K-L. Areerak, A. Srikaew

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The paper presents the applications of artificial intelligence technique called adaptive tabu search to design the controller of a buck converter. The averaging model derived from the DQ and generalized state-space averaging methods is applied to simulate the system during a searching process. The simulations using such averaging model require the faster computational time compared with that of the full topology model from the software packages. The reported model is suitable for the work in the paper in which the repeating calculation is needed for searching the best solution. The results will show that the proposed design technique can provide the better output waveforms compared with those designed from the classical method.

Keywords: Buck converter, adaptive tabu search, DQ method, generalized state-space averaging method, modeling and simulation

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Authors: Yufang Cheng, Hsiu-Hua Yang

Abstract:

This work develops a novel intelligent “model of dynamic decision-making" usingcell assemblies network architecture in robot's movement. The “model of dynamic decision-making" simulates human decision-making, and follows commands to make the correct decisions. The cell assemblies approach consisting of fLIF neurons was used to implement tasks for finding targets and avoiding obstacles. Experimental results show that the cell assemblies approach of can be employed to efficiently complete finding targets and avoiding obstacles tasks and can simulate the human thinking and the mode of information transactions.

Keywords: Cell assemblies, fLIF, Hebbian learning rule.

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Authors: Erika Martinez Ramirez, Rene V. Mayorga

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In our modern world, more physical transactions are being substituted by electronic transactions (i.e. banking, shopping, and payments), many businesses and companies are performing most of their operations through the internet. Instead of having a physical commerce, internet visitors are now adapting to electronic commerce (e-Commerce). The ability of web users to reach products worldwide can be greatly benefited by creating friendly and personalized online business portals. Internet visitors will return to a particular website when they can find the information they need or want easily. Dealing with this human conceptualization brings the incorporation of Artificial/Computational Intelligence techniques in the creation of customized portals. From these techniques, Fuzzy-Set technologies can make many useful contributions to the development of such a human-centered endeavor as e-Commerce. The main objective of this paper is the implementation of a Paradigm for the Intelligent Design and Operation of Human-Computer interfaces. In particular, the paradigm is quite appropriate for the intelligent design and operation of software modules that display information (such Web Pages, graphic user interfaces GUIs, Multimedia modules) on a computer screen. The human conceptualization of the user personal information is analyzed throughout a Cascaded Fuzzy Inference (decision-making) System to generate the User Ascribe Qualities, which identify the user and that can be used to customize portals with proper Web links.

Keywords: Fuzzy Logic, Internet, Electronic Commerce, Intelligent Portals, Electronic Shopping.

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Authors: A. Radzevičius, P. Viškelis, J. Viškelis, R. Bobinaitė, R. Karklelienė, D. Juškevičienė

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Two cultivars ('Rutuliai', 'Saint Perrie') and five hybrids ('Tolstoi', 'Brooklyn', 'Tocayo', 'Benito', 'Tourist') of edible tomato (Lycopersicon esculentum Mill.) were investigated at the LRCAF Institute of Horticulture. The following fruit quality parameters were evaluated: the amount of lycopene, β-carotene, ascorbic acid, total and inverted sugar, sucrose, dry matter soluble solids in fresh tomato matter, also were determined fruit skin and flesh firmness, color indexes (CIE L*a*b*) and calculated hue angle (h°) with chroma (C).

Keywords: Carotenoids, cultivar, nutrition, tomato.

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Authors: N. A. Muhamad, S.A.M. Ali

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Condition monitoring of electrical power equipment has attracted considerable attention for many years. The aim of this paper is to use Labview with Fuzzy Logic controller to build a simulation system to diagnose transformer faults and monitor its condition. The front panel of the system was designed using LabVIEW to enable computer to act as customer-designed instrument. The dissolved gas-in-oil analysis (DGA) method was used as technique for oil type transformer diagnosis; meanwhile terminal voltages and currents analysis method was used for dry type transformer. Fuzzy Logic was used as expert system that assesses all information keyed in at the front panel to diagnose and predict the condition of the transformer. The outcome of the Fuzzy Logic interpretation will be displayed at front panel of LabVIEW to show the user the conditions of the transformer at any time.

Keywords: LabVIEW, Fuzzy Logic, condition monitoring, oiltransformer, dry transformer, DGA, terminal values.

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Authors: Mehrdad Mahmudizad, Roya Ahmadi Ahangar

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This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.

Keywords: Load Frequency Control, Fuzzy-PID controller, Type 2 fuzzy system, Harmony Search algorithm.

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Authors: Danielle Reichel, Antoine Druilhe, Tuan Dang

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Traditional development of wireless sensor network mote is generally based on SoC1 platform. Such method of development faces three main drawbacks: lack of flexibility in terms of development due to low resource and rigid architecture of SoC; low capability of evolution and portability versus performance if specific micro-controller architecture features are used; and the rapid obsolescence of micro-controller comparing to the long lifetime of power plants or any industrial installations. To overcome these drawbacks, we have explored a new approach of development of wireless sensor network mote using a hybrid FPGA technology. The application of such approach is illustrated through the implementation of an innovative wireless sensor network protocol called OCARI.

Keywords: Hybrid FPGA, Embedded system, Mote, flexibility, durability, OCARI protocol, SoC, Wireless Sensor Network

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Authors: Jenn-Yih Chen, Bean-Yin Lee, Yuan-Chuan Hsu, Jui-Cheng Lin, Kuang-Chyi Lee

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In this paper, a sliding mode control method based on the passivity approach is proposed to control the position of surface-mounted permanent magnet synchronous motors (PMSMs). Firstly, the dynamics of a PMSM was proved to be strictly passive. The position controller with an adaptive law was used to estimate the load torque to eliminate the chattering effects associated with the conventional sliding mode controller. The stability analysis of the overall position control system was carried out by adopting the passivity theorem instead of Lyapunov-type arguments. Finally, experimental results were provided to show that the good position tracking can be obtained, and exhibit robustness in the variations of the motor parameters and load torque disturbances.

Keywords: Adaptive law, passivity theorem, permanent magnet synchronous motor, sliding mode control.

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Authors: F. Matusek, G. Pujolle, R. Reda

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Shadow detection is still considered as one of the potential challenges for intelligent automated video surveillance systems. A pre requisite for reliable and accurate detection and tracking is the correct shadow detection and classification. In such a landscape of conditions, privacy issues add more and more complexity and require reliable shadow detection. In this work the intertwining between security, accuracy, reliability and privacy is analyzed and, accordingly, a novel architecture for Privacy Enhancing Video Surveillance (PEVS) is introduced. Shadow detection and masking are dealt with through the combination of two different approaches simultaneously. This results in a unique privacy enhancement, without affecting security. Subsequently, the methodology was employed successfully in a large-scale wireless video surveillance system; privacy relevant information was stored and encrypted on the unit, without transferring it over an un-trusted network.

Keywords: Video Surveillance, Intelligent Video Surveillance, Physical Security, WSSU, Privacy, Shadow Detection.

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Authors: Konstantinos C. Giotopoulos, Christos E. Alexakos, Grigorios N. Beligiannis, Spiridon D.Likothanassis

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In this contribution an innovative platform is being presented that integrates intelligent agents and evolutionary computation techniques in legacy e-learning environments. It introduces the design and development of a scalable and interoperable integration platform supporting: I) various assessment agents for e-learning environments, II) a specific resource retrieval agent for the provision of additional information from Internet sources matching the needs and profile of the specific user and III) a genetic algorithm designed to extract efficient information (classifying rules) based on the students- answering input data. The agents are implemented in order to provide intelligent assessment services based on computational intelligence techniques such as Bayesian Networks and Genetic Algorithms. The proposed Genetic Algorithm (GA) is used in order to extract efficient information (classifying rules) based on the students- answering input data. The idea of using a GA in order to fulfil this difficult task came from the fact that GAs have been widely used in applications including classification of unknown data. The utilization of new and emerging technologies like web services allows integrating the provided services to any web based legacy e-learning environment.

Keywords: Bayesian Networks, Computational Intelligencetechniques, E-learning legacy systems, Service Oriented Integration, Intelligent Agents, Genetic Algorithms.

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Authors: Chin-Ming Hong, Chin-Teng Lin, Chao-Yen Huang, Yi-Ming Lin

Abstract:

In this article, we propose an Intelligent Medical Diagnostic System (IMDS) accessible through common web-based interface, to on-line perform initial screening for osteoporosis. The fundamental approaches which construct the proposed system are mainly based on the fuzzy-neural theory, which can exhibit superiority over other conventional technologies in many fields. In diagnosis process, users simply answer a series of directed questions to the system, and then they will immediately receive a list of results which represents the risk degrees of osteoporosis. According to clinical testing results, it is shown that the proposed system can provide the general public or even health care providers with a convenient, reliable, inexpensive approach to osteoporosis risk assessment.

Keywords: BMD, osteoporosis, IMDS, fuzzy-neural theory, web interface.

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Authors: Seyedeh Mozhgan Seyed-Talebi, Javad Beheshtian

Abstract:

The toxicity of lead associated with the lifecycle of perovskite solar cells (PSCs( is a serious concern which may prove to be a major hurdle in the path toward their commercialization. The current proposed lead-free PSCs including Ag(I), Bi(III), Sb(III), Ti(IV), Ge(II), and Sn(II) low-toxicity cations are still plagued with the critical issues of poor stability and low efficiency. This is mainly because of their chemical stability. In the present research, utilization of all inorganic CsSnGeI₃ based materials offers the advantages to enhance resistance of device to degradation, reduce the cost of cells, and minimize the carrier recombination. The presence of inorganic halide perovskite improves the photovoltaic parameters of PCSs via improved surface coverage and stability. The inverted structure of simulated devices using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves TCOHTL/Perovskite/ETL/Au contact layer. PEDOT:PSS, PCBM, and CsSnGeI₃ used as hole transporting layer (HTL), electron transporting layer (ETL), and perovskite absorber layer in the inverted structure for the first time. The holes are injected from highly stable and air tolerant Sn_0.5Ge_0.5I₃ perovskite composition to HTM and electrons from the perovskite to ETL. Simulation results revealed a great dependence of power conversion efficiency (PCE) on the thickness and defect density of perovskite layer. Here the effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnGeI₃ based perovskite devices is investigated. Comparison between simulated CsSnGeI₃ based PCSs and similar real testified devices with spiro-OMeTAD as HTL showed that the extraction of carriers at the interfaces of perovskite absorber depends on the energy level mismatches between perovskite and HTL/ETL. We believe that optimization results reported here represent a critical avenue for fabricating the stable, low-cost, efficient, and eco-friendly all-inorganic Cs-Sn-Ge based lead-free perovskite devices.

Keywords: Hole transporting layer, lead-free, perovskite Solar cell, SCAPS-1D, Sn-Ge based material.

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Authors: M. Zerikat, M. Bendjebbar, N. Benouzza

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In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.

Keywords: Induction motor, fuzzy-logic control, neural network control, indirect field oriented control.

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Authors: W. Chayinthu, K-N. Areerak, K-L. Areerak, A. Srikaew

Abstract:

This paper presents the optimal controller design of the generator control unit in the aircraft power system. The adaptive tabu search technique is applied to tune the controller parameters until the best terminal output voltage of generator is achieved. The output response from the system with the controllers designed by the proposed technique is compared with those from the conventional method. The transient simulations using the commercial software package show that the controllers designed from the adaptive tabu search algorithm can provide the better output performance compared with the result from the classical method. The proposed design technique is very flexible and useful for electrical aircraft engineers.

Keywords: Cascade PI controllers, DQ method, Adaptive tabusearch, Generator control unit, Aircraft power system, Modeling, Simulation, Artificial Intelligence.

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Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

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In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: Prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy.

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Authors: Nhon Do, Tam Pham

Abstract:

Knowledge bases are basic components of expert systems or intelligent computational programs. Knowledge bases provide knowledge, events that serve deduction activity, computation and control. Therefore, researching and developing of models for knowledge representation play an important role in computer science, especially in Artificial Intelligence Science and intelligent educational software. In this paper, the extensive deduction computational model is proposed to design knowledge bases whose attributes are able to be real values or functional values. The system can also solve problems based on knowledge bases. Moreover, the models and algorithms are applied to produce the educational software for solving alternating current problems or solving set of equations automatically.

Keywords: Educational software, artificial intelligence, knowledge base systems, knowledge representation.

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Authors: Li Jie, Zhang Wei

Abstract:

In this paper, the problem of posture stabilization for a kinematic model of differential drive robots is studied. A more complex model of the kinematics of differential drive robots is used for the design of stabilizing control. This model is formulated in terms of the physical parameters of the system such as the radius of the wheels, and velocity of the wheels are the control inputs of it. In this paper, the framework of Lyapunov-based control design has been used to solve posture stabilization problem for the comprehensive model of differential drive robots. The results of the simulations show that the devised controller successfully solves the posture regulation problem. Finally, robustness and performance of the controller have been studied under system parameter uncertainty.

Keywords: Differential drive robots, nonlinear control, Lyapunov-based control design, posture regulation.

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Authors: Van Nhan Nguyen, Harald Holone

Abstract:

Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.

Keywords: Automatic Speech Recognition, ASR, Air Traffic Control, ATC.

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Authors: A. A. Jafari, A. M. Khoshnood, J. Roshanian

Abstract:

Attitude control of aerospace system with liquid containers may face to a problem associate with fuel sloshing. The sloshing phenomena can degrade the stability of control system and in the worst case, interaction between the attitude control system and fuel vibration leading to resonance. In this paper, a full process of nonlinear dynamic modeling of an aerospace launch vehicle with fuel sloshing is given. Then, a new control system based on model reference adaptive filter is proposed and its algorithm is extracted. This controller implemented on the main attitude control system. Finally, numerical simulation of nonlinear model and control system is carried out to examine the performance of the new controller. Results of simulations show that the inconvenient effects of the fuel sloshing by augmenting this control system are reduced and attitude control system performs, satisfactorily.

Keywords: nonlinear dynamic modeling, fuel sloshing, vibration control, model reference, adaptive filter

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Authors: Yuri Boiko, Iluju Kiringa, Tet Yeap

Abstract:

Current drainage attack suggested previously is further studied in regular settings of closed-loop controlled Brushless DC (BLDC) motor with Kalman filter in the feedback loop. Modeling and simulation experiments are conducted in a MATLAB environment, implementing the closed-loop control model of BLDC motor operation in position sensorless mode under Kalman filter drive. The current increase in the motor windings is caused by the controller (p-controller in our case) affected by false data injection of substitution of the angular velocity estimates with distorted values. Operation of multiplication to distortion coefficient, values of which are taken from the distortion function synchronized in its periodicity with the rotor’s position change. A saw function with a triangular tooth shape is studied herewith for the purpose of carrying out the bias injection with current drainage consequences. The specific focus here is on how the asymmetry of the tooth in the saw function affects the flow of current drainage. The purpose is two-fold: (i) to produce and collect the signature of an asymmetric saw in the attack for further pattern recognition process, and (ii) to determine conditions of improving stealthiness of such attack via regulating asymmetry in saw function used. It is found that modification of the symmetry in the saw tooth affects the periodicity of current drainage modulation. Specifically, the modulation frequency of the drained current for a fully asymmetric tooth shape coincides with the saw function modulation frequency itself. Increasing the symmetry parameter for the triangle tooth shape leads to an increase in the modulation frequency for the drained current. Moreover, such frequency reaches the switching frequency of the motor windings for fully symmetric triangular shapes, thus becoming undetectable and improving the stealthiness of the attack. Therefore, the collected signatures of the attack can serve for attack parameter identification via the pattern recognition route.

Keywords: Bias injection attack, Kalman filter, BLDC motor, control system, closed loop, P-controller, PID-controller, current drainage, saw-function, asymmetry.

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Authors: W. K. Wong, Z. X. Guo, P.Y. Mok

Abstract:

This paper presents a multi-objective order allocation planning problem with the consideration of various real-world production features. A novel hybrid intelligent optimization model, integrating a multi-objective memetic optimization process, a Monte Carlo simulation technique and a heuristic pruning technique, is proposed to handle this problem. Experiments based on industrial data are conducted to validate the proposed model. Results show that (1) the proposed model can effectively solve the investigated problem by providing effective production decision-making solutions, which outperformsan NSGA-II-based optimization process and an industrial method.

Keywords: Multi-objective order allocation planning, Pareto optimization, Memetic algorithm, Mento Carlo simulation

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Authors: M Nayeripour, E. Azad, A. Roosta, T. Niknam

Abstract:

In this paper, the transformers over-load problem of Shiraz substation in Fars Regional Electric Company (FREC) is investigated for a period of three years plan. So the suggestions for using phase shifting transformer (PST) and unified power flow controller (UPFC) in order to solve this problem are examined in details and finally, some economical and practical designs will be given in order to solve the related problems. Practical consideration and using the basic and fundamental concept of powers in transmission lines in order to find the economical design are the main advantages of this research. The simulation results of the integrated overall system with different designs compare them base on economical and practical aspects to solve the over-load and loss-reduction.

Keywords: Congestion management, Phase shifting transformer(PST), Unified power flow controller (UPFC), Transmission lines.

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Authors: Sidhartha Panda, C. Ardil

Abstract:

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to coordinately design multiple power system stabilizers (PSS) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem and PSO is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented for various severe disturbances and small disturbance at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.

Keywords: Low frequency oscillations, Particle swarm optimization, power system stability, power system stabilizer, multimachine power system.

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Authors: Devdutt, M. L. Aggarwal

Abstract:

In this paper, passenger ride comfort issues are studied taking active quarter car model with three degrees of freedom. A hybrid fuzzy – PID controller with coupled rules (HFPIDCR) is designed for vibration control of passenger seat. Three different control strategies are considered. In first case, main suspension is controlled. In second case, passenger seat suspension is controlled. In third case, both main suspension and passenger seat suspensions are controlled. Passenger seat acceleration and displacement results are obtained using bump and sinusoidal type road disturbances. Finally, obtained simulation results of designed uncontrolled and controlled quarter car models are compared and discussed to select best control strategy for achieving high level of passenger ride comfort.

Keywords: Active suspension system, HFPIDCR controller, passenger ride comfort, quarter car model.

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Authors: Maziar Ahmad Sharbafi, Caro Lucas, Abolfazel Toroghi Haghighat, Omid AmirGhiasvand, Omid Aghazade

Abstract:

RoboCup Rescue simulation as a large-scale Multi agent system (MAS) is one of the challenging environments for keeping coordination between agents to achieve the objectives despite sensing and communication limitations. The dynamicity of the environment and intensive dependency between actions of different kinds of agents make the problem more complex. This point encouraged us to use learning-based methods to adapt our decision making to different situations. Our approach is utilizing reinforcement leaning. Using learning in rescue simulation is one of the current ways which has been the subject of several researches in recent years. In this paper we present an innovative learning method implemented for Police Force (PF) Agent. This method can cope with the main difficulties that exist in other learning approaches. Different methods used in the literature have been examined. Their drawbacks and possible improvements have led us to the method proposed in this paper which is fast and accurate. The Brain Emotional Learning Based Intelligent Controller (BELBIC) is our solution for learning in this environment. BELBIC is a physiologically motivated approach based on a computational model of amygdale and limbic system. The paper presents the results obtained by the proposed approach, showing the power of BELBIC as a decision making tool in complex and dynamic situation.

Keywords: Emotional learning, rescue, simulation environment, RoboCup, multi-agent system.

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Authors: Pranee Pathomchaiwat

Abstract:

The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).

Keywords: English language, language learning strategies, English learning achievement, students majoring in English, Business English

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Authors: T. R. Alencar, P. T. Leite

Abstract:

Several optimization algorithms specifically applied to the problem of Operation Planning of Hydrothermal Power Systems have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. Thus, this paper presents the development of a computational tool for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique, Genetic Algorithms and programming language Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: Energy, Optimization, Hydrothermal Power Systemsand Genetic Algorithms

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Authors: Amon Tunwannarux, Supanunt Tunwannarux

Abstract:

This paper presents design features of a rescue robot, named CEO Mission II. Its body is designed to be the track wheel type with double front flippers for climbing over the collapse and the rough terrain. With 125 cm. long, 5-joint mechanical arm installed on the robot body, it is deployed not only for surveillance from the top view but also easier and faster access to the victims to get their vital signs. Two cameras and sensors for searching vital signs are set up at the tip of the multi-joint mechanical arm. The third camera is at the back of the robot for driving control. Hardware and software of the system, which controls and monitors the rescue robot, are explained. The control system is used for controlling the robot locomotion, the 5-joint mechanical arm, and for turning on/off devices. The monitoring system gathers all information from 7 distance sensors, IR temperature sensors, 3 CCD cameras, voice sensor, robot wheels encoders, yawn/pitch/roll angle sensors, laser range finder and 8 spare A/D inputs. All sensors and controlling data are communicated with a remote control station via IEEE 802.11b Wi-Fi. The audio and video data are compressed and sent via another IEEE 802.11g Wi-Fi transmitter for getting real-time response. At remote control station site, the robot locomotion and the mechanical arm are controlled by joystick. Moreover, the user-friendly GUI control program is developed based on the clicking and dragging method to easily control the movement of the arm. Robot traveling map is plotted from computing the information of wheel encoders and the yawn/pitch data. 2D Obstacle map is plotted from data of the laser range finder. The concept and design of this robot can be adapted to suit many other applications. As the Best Technique awardee from Thailand Rescue Robot Championship 2006, all testing results are satisfied.

Keywords: Controlling, monitoring, rescue robot, mechanicalarm.

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

Abstract:

Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: Deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator.

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