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IEEE International Conference on Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)

作者： Mohideen, K. Asan Mathi, K. Valar Kalasalingam Univ Dept Instrumentat & Control Engn Anandnagar 626126 Krishnankoil India

ISBN: (纸本)9781467350372;9781467350365;9781467350358

Level control is an important application in process industry. Traditionally PID controller has been used for this purpose. As level process is non-linear, whenever the process is operated outside a linearized region the PID controller parameters need to be tuned. In this case adaptive controllers are more suited. The objective of the paper is to apply a Modified Model Reference Adaptive Controller (MRAC) to control level in a hybrid tank system in regulatory mode and compare its disturbance rejection capability with that of a standard direct MRAC and a well-designed PID controller. In this paper, a direct MRAC, two types of modified MRACs and a PID controller are designed for a hybrid tank process and their performances are compared while operated in regulatory mode. The results show that the Modified MRACs give better disturbance rejection when compared with the MRAC and the PID controller. It is concluded that the Modified MRACs can be used to obtain very good regulatory performance during the control of nonlinear processes.

关键词： Disturbance rejection Model Reference Adaptive Controller Modified MRAC nonlinear process control real-coded genetic algorithm

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Power System Stability Enhancement With genetically Optimized SVC Controller

Power System Stability Enhancement With Genetically Optimize...

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International Conference on Power, Energy and Control (ICPEC)

作者： Hameed, Salman Garg, Pallavi Varshney, Santosh Kumar Aligarh Muslim Univ Dept Elect Engn ZH Coll Engg & Tech Aligarh Uttar Pradesh India

ISBN: (纸本)9781467360302;9781467360272

Multi-machine power system stability improvement by tuning of Static Var Compensator (SVC)-based controller parameters is investigated in the proposed method. The design problem is formulated as an optimization problem with a time-domain simulation-based objective function and real-coded genetic algorithm (RCGA) is used for searching optimal controller parameters. A multi-machine power system model is developed using MATLAB's SIMULINK which incorporates SVC Controller. A fault is created on the transmission line. The simulation results of the multi-machine power system without SVC Controller and with SVC Controller are presented. The simulation results are analyzed which shows that the power system becomes unstable on the occurrence of the fault if SVC controller is not used. This paper shows the effectiveness of the proposed design. The proposed method enhances the multi-machine power system stability.

关键词： Power System Stability Damping of power oscillations SVC real-coded genetic algorithm multi-machine power system

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Dental Caries Degree Detection based on Fuzzy Cognitive Maps and genetic algorithm 26

Dental Caries Degree Detection based on Fuzzy Cognitive Maps...

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26th Iranian Conference on Electrical Engineering (ICEE)

作者： Haghanifar, Arman Amirkhani, Abdollah Mosavi, Mohammad R. Iran Univ Sci & Technol Dept Elect Engn Tehran *** Iran

ISBN: (纸本)9781538649169

Dental caries is the most common infectious disease in humans, which affects 97% of the population in their lifetimes. In this article, fuzzy cognitive maps (FCMs) are applied to classify patients in terms of their personal risk of dental caries. Two approaches are discussed for developing FCMs. At first, causal relations between concepts and their weights are defined based on the domain experts. Then, these causal weights are determined by means of the real-coded genetic algorithm (RCGA) and historical data, without the intervention of experts. These two FCMs have been compared by categorizing 86 sample patients into two classes: 'carious' and 'healthy'. Although the conventional FCM has successfully categorized 67.44% of the cases in correct classes, the RCGA based FCM hits the 83.72% correct classification rate. Results show the efficiency of RCGA based FCM in comparison with the conventional FCM.

关键词： fuzzy cognitive maps dental caries real-coded genetic algorithm patient classification

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Evolutionary particle swarm optimization (EPSO) - Estimation of optimal PSO parameters by GA

Evolutionary particle swarm optimization (EPSO) - Estimation...

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International Multiconference of Engineers and Computer Scientists

作者： Zhang, Hong Ishikawa, Masumi Kyutech Inst Technol Grad Sch Life Sci & Syst Engn Dept Brain Sci Engn 2-4 Hibikino Kitakyushu Fukuoka 8080196 Japan

ISBN: (纸本)9789889867140

Particle Swarm Optimization (PSO) is a stochastic and population-based search algorithm that demonstrates its effctiveness in solving complex nonlinear optimization problems. Although the original PSO is very simple and effective, how to determine appropriate values of parameters in PSO is yet to be found. This paper proposes a novel method called evolutionary PSO, which estimates values of parameters in PSO for effectively finding globally optimal parameter values by a real-coded genetic a gorithm. A crucial idea here is to adopt a temporary cumulative fitness instead of instantaneous fitness in a realcoded genetic algorithm for evaluating the performance of the PSO. It provides a useful measure that efficiently determines appropriate values of parameters in PSO. To demonstrate the effectiveness of the proposed method, we implement a simple computer experiment on a 2-dimensional optimization problem, and analyze the characteristics of dependency on initial condition.

关键词： particle swarm optimization real-coded genetic algorithm elitism strategy

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Convergence Acceleration of Multi-material Structural Optimization Method Based on Fourier Series Expansion for Outer-rotor Permanent Magnet Synchronous motor 24

Convergence Acceleration of Multi-material Structural Optimi...

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24th International Conference on Electrical Machines and Systems (ICEMS)

作者： Koda, Riku Okmoto, Yoshifumi Hosei Univ Dept Elect & Elect Engn Tokyo Japan

ISBN: (纸本)9788986510218

Since the topology optimization (TO) has a higher degree of structural freedom than the shape optimization, the TO is actively applied to the motor design. Although the convergence speed of TO based on the sensitivity analysis, which is the gradient of objective function and constraint conditions with respect to the design variables, is generally faster than that TO based on evolutionary algorithm (TOEA), TOEA has the affinity to the optimization problem with many constraint conditions. In this paper, to improve the convergence characteristic of TOEA, the method to gradually increase the expansion order of Fourier series which models the magnetic structure in the design domain is proposed. When the order of Fourier series expansion is increased in the process of TOEA, the integrity of magnetic structures between lower and higher order of Fourier series is maintained by solving the least square problem to minimize the function expressing the degree of disagreement. The performance of the proposed TOEA is demonstrated in the permanent magnet motor and compared with the conventional TOEA and gradient-based TO.

关键词： Fourier series expansion gradient-based topology optimization real-coded genetic algorithm SPM motor

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Design and implementation of gain scheduling decentralized PI/PID controller for the fluid catalytic cracking unit

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BIOMEDICAL SIGNAL PROCESSING AND CONTROL 2022年第0期77卷 000-000页

作者： Puviyarasi, B. Murukesh, C. Alagiri, M. Anna Univ Sri Sairam Engn Coll Dept Elect & Instrumentat Engn Chennai 600 044 Tamil Nadu India Anna Univ Velammal Engn Coll Dept Elect & Elect Engn Chennai 600066 Tamil Nadu India SRM Inst Sci & Technol Dept Phys & Nanotechnol Chengalpattu 603203 Tamil Nadu India

Fluid Catalytic Cracking Unit (FCCU) is a technique where raw crude oil is transformed into lighter petroleum products. It is a challenging problem in the refining industry. The FCCU is a non-linear and interactive process as they are interdependent on one another. This process also describes the intercommunication of the controllers by providing a decentralized controller. The Proportional-Integral-Derivative controller (PID) is an easy way of controlling and implementing the process. In this paper, the performance of FCCU with Gain Scheduling Decentralized Proportional-Integral (GSD-PI) and Gain Scheduling Decentralized PID (GSD-PID) controllers are compared, and the output will prove that the GSD-PID controller is well organized over GSD-PI Controller. The result shows that the GSD-PID controller exhibits the best performance with evaluation criteria like Integral square error, Integral absolute error, and Integral time absolute error. A small change to the PI Controller will drastically affect the process but in PID there is no effect over them. The real-coded genetic algorithm (GA) is utilized to determine optimal values for GSD-PID and GSD-PI controllers. The executed output proves that the real-coded GA tuned GSD-PID control scheme has realized the performance by the system with smaller overshoot, effects of interaction is minimum and good disturbance rejection are noted.

关键词： Gain scheduling decentralized PID controller Fluid catalytic cracking unit Non-linear Interacting process real-coded genetic algorithm

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Developing a neural network and real genetic algorithm combined tool for an engine test bed

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2006年第D12期220卷 1737-1753页

作者： Wu, Mian Hong Lin, Wanchang Duan, Shang Y. Univ Derby Sch Art Design & Technol Derby DE22 1GB England Univ Wales Inst Biol Sci Aberystwyth Ceredigion Wales Land Rover Ltd Gaydon Test Ctr Warwick England

In the automotive industry, engine test engineers are required to deal with a huge quantity of experimental data obtained from engine test beds each day. Those data must be analysed to evaluate engine performance and to guide further engine test operations. In order to improve efficiency and reduce expenditure of time in engine testing, it is very important for engine test bed controllers to develop a mathematical model from existing engine test data. This paper presents an investigation of a neural network-genetic algorithm (GA) combined tool for engine modelling. In the modelling tool, a real-coded GA has been employed to train three different groups of neural networks (a multilayer perceptron group, a radial basis function group, and a bar function networks group) and then finally to find the most suitable neural network model for engine modelling. The experimental results given in this paper show that the proposed tool has been successfully used for Rover engine testing.

关键词： evolutionary neural networks real-coded genetic algorithm engine modelling engine calibration

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Energy-saving trajectory planning for a toggle mechanism driven by a PMSM

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IFAC Proceedings Volumes 2013年第5期46卷 628-635页

作者： Yi-Lung Hsu Ming-Shyan Huang Rong-Fong Fung Institute of Engineering Science and Technology National Kaohsiung First University of Science and Technology 1 University Road Yenchau Kaohsiung 824 TAIWAN (Tel: +886-7-6011000 ext 2238 Department of Mechanical & Automation Engineering National Kaohsiung First University of Science and Technology 1 University Road Yenchau Kaohsiung 824 TAIWAN (Tel: +886-7-6011000 ext 2238

This paper proposes a methodology to plan an energy-saving trajectory for a toggle mechanism by a permanent magnet synchronous motor (PMSM). The system is first identified by the numerical methods. The trajectory is described by a high-degree polynomial, which is a point-to-point (PTP) function and satisfies the end conditions of displacement, velocity, acceleration and jerk at the initial and final times. The real-coded genetic algorithm (RGA) is employed to determine the coefficients of the polynomial with the fitness function, which is the inverse of the absolute value of the input electric energy. In this paper, some discussions for planning an energy-saving trajectory are made, and three cases of the fitness functions are used.

关键词： Energy-saving Point-to-point trajectory real-coded genetic algorithm Toggle mechanism

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How to Infer the Interactive Large Scale Regulatory Network in ‘Omic’ Studies

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Procedia Computer Science 2013年 23卷 44-52页

作者： Asako Komori Yukihiro Maki Isao Ono Masahiro Okamoto Department of Bioinformatics Graduate School of Systems Life Sciences Kyushu University Fukuoka 8128582 Japan Synthetic Systems Biology Research Center Kyushu University Fukuoka 8128582 Japan Graduate School of Computational Intelligence and Systems Science Tokyo Institute of Technology Tokyuo 2268502 Japan

Inferring regulatory networks in genetic systems and metabolic pathways is one of the most important problems in systems biology. Inferring network structure from experimentally observed time series data is an inverse problem. To deal with such problems, we have developed an efficient numerical optimization method called the hybrid method, which is a combination of real-coded genetic algorithms and the modified Powell method using the S-system representation. In general, a large regulatory network comprises numerous interactive system components and requires the optimization of a large number of parameters with non-zero interaction coefficients between them. To date, we have succeeded in optimizing 272 real-valued parameters using the hybrid method. Although compared with conventional numerical optimization methods, the hybrid method is powerful but is still insufficient for inferring large-scale networks. Here we discuss the inference of interactive large-scale regulatory networks in ‘omics’ studies based on our hybrid numerical optimization method.

关键词： inverse problem S-system formalism gene regulatory network system identification real-coded genetic algorithm

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Robust design method and thermostatic experiment for multiple piezoelectric vibration absorber system

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SMART MATERIALS AND STRUCTURES 2015年第12期24卷

作者： Nambu, Yohsuke Takashima, Toshihide Inagaki, Akiya Osaka Prefecture Univ Grad Sch Engn Naka Ku Sakai Osaka 5998531 Japan Osaka Prefecture Univ Dept Aerosp Engn Naka Ku Sakai Osaka 5998531 Japan Tokyo Inst Technol Dept Mech & Aerosp Engn Meguro Ku Tokyo 1528552 Japan

This paper examines the effects of connecting multiplexing shunt circuits composed of inductors and resistors to piezoelectric transducers so as to improve the robustness of a piezoelectric vibration absorber (PVA). PVAs are well known to be effective at suppressing the vibration of an adaptive structure;their weakness is low robustness to changes in the dynamic parameters of the system, including the main structure and the absorber. In the application to space structures, the temperature-dependency of capacitance of piezoelectric ceramics is the factor that causes performance reduction. To improve robustness to the temperature-dependency of the capacitance, this paper proposes a multiple-PVA system that is composed of distributed piezoelectric transducers and several shunt circuits. The optimization problems that determine both the frequencies and the damping ratios of the PVAs are multi-objective problems, which are solved using a real-coded genetic algorithm in this paper. A clamped aluminum beam with four groups of piezoelectric ceramics attached was considered in simulations and experiments. Numerical simulations revealed that the PVA systems designed using the proposed method had tolerance to changes in the capacitances. Furthermore, experiments using a thermostatic bath were conducted to reveal the effectiveness and robustness of the PVA systems. The maximum peaks of the transfer functions of the beam with the open circuit, the single-PVA system, the double-PVA system, and the quadruple-PVA system at 20 degrees C were 14.3 dB, -6.91 dB, -7.47 dB, and -8.51 dB, respectively. The experimental results also showed that the multiple-PVA system is more robust than a single PVA in a variable temperature environment from -10 degrees C to 50 degrees C. In conclusion, the use of multiple PVAs results in an effective, robust vibration control method for adaptive structures.

关键词： dynamic vibration absorber piezoelectric material real-coded genetic algorithm robust design thermal dependency

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