• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.384-386
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• 2009

This paper introduces an effectively optimized Fuzzy model identification by means of complex and nonlinear system applying PSO algorithm. In other words, we use PSO(Particle Swarm Optimization) for identification of Fuzzy model structure and parameter. PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. This paper identifies the premise part parameters and the consequence structures that have many effects on Fuzzy system based on PSO. In the premise parts of the rules, we use triangular. Finally we evaluate the Fuzzy model that is widely used in the standard model of gas data and sew data.

• Geomechanics and Engineering
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• v.27 no.5
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• pp.527-535
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• 2021

The creep characteristics of rock is of great significance for the study of long-term stability of engineering, so it is necessary to carry out indoor creep test and creep model of rock. First of all, in different water-bearing state and different positive pressure conditions, the granite is graded loaded to conduct indoor shear creep test. Through the test, the shear creep characteristics of granite are obtained. According to the test results, the stress-strain isochronous curve is obtained, and then the long-term strength of granite under different conditions is determined. Then, the fractional-order calculus software element is introduced, and it is connected in series with the spring element and the nonlinear viscoplastic body considering the creep acceleration start time to form a nonlinear viscoplastic creep model with fewer elements and fewer parameters. Finally, based on the shear creep test data of granite, using the nonlinear curve fitting of Origin software and Levenberg-Marquardt optimization algorithm, the parameter fitting and comparative analysis of the nonlinear creep model are carried out. The results show that the test data and the model curve have a high degree of fitting, which further explains the rationality and applicability of the established nonlinear visco-elastoplastic creep model. The research in this paper can provide certain reference significance and reference value for the study of nonlinear creep model of rock in the future.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.69-75
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• 2006

This paper deals with the optimum design solution on reduction of torque ripple for a Synchronous Reluctance Motor with concentrated winding using response surface methodology. The coupled Finite Elements Analysis (FEA) & Preisach model have been used to evaluate the nonlinear solution. Comparisons are given with characteristics of a SynRM according to the stator winding, slot number, open width of slot, slot depth, teeth width variation in concentrated winding SynRM, respectively. This paper presents an optimization procedure using Response Surface Methodology (RSM) to determine design parameters for reducing torque ripple. RSM has been achieved to use the experimental design method in combination with finite Element Method (FEM) and well adapted to make analytical model for a complex problem considering a lot of interaction of design variables. Moreover, Sequential Quadratic Problem (SQP) method is used to solve the resulting of constrained nonlinear optimization problem.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.137-146
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• 2004

This is the second of two companion papers concerned with the analysis and design of a pneumatic vibration isolation system. The properties of the system are clarified by observation of the transmissibility surface calculated by the models and algorithm developed in the first paper of this research. It Is shown that the nonlinear model proposed in this research is more closer to experimental results than the linear model that have been used in previous studies. The design optimization of the major design variables that affect the performance of the system is achieved by using the condition for attenuation, disturbance rejection and maximum damping in resonance peak. The design space search method is adopted for the optimization of the orifice area. The models, transmissibility calculation algorithms and design optimization techniques developed in this research are shown to be greatly helpful to the optimal design of the pneumatic vibration isolation system by experiment.

• Structural Engineering and Mechanics
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• v.20 no.2
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• pp.161-172
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• 2005

This paper presents the section model for analysis of RC circular tower structures based on nonlinear material laws. The governing equations for normal strains due to the bending moment and the normal force are derived in the case when openings are located symmetrically in respect to the bending direction. In this approach the additional reinforcement at openings is also taken into account. The mathematical model is expressed in the form of a set of nonlinear equations which are solved by means of the minimization of the sums of the second powers of the residuals. For minimization the BFGS quasi-Newton and/or Hooke-Jeeves local minimizers suitably modified are applied to take into account the box constraints on variables. The model is verified on the set of data encountered in engineering practice. The numerical examples illustrate the effects of the loading eccentricity and size of the opening on the strains and stresses in concrete and steel in the cross-sections under consideration. Calculated results indicate that the additional reinforcement at the openings increases the resistance capacity of the section by several percent.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.911-914
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• 2005

Soft tissue characterization and modeling based on living tissues has been investigated in order to provide a more realistic behavior in a virtual reality based surgical simulation. In this paper, we characterize the nonlinear viscoelastic properties of intra-abdominal organs using the data from in vivo animal experiments and inverse FE parameter estimation algorithm. In the assumptions of quasi-linear-viscoelastic theory, we estimated the nonlinear material parameters to provide a physically based simulation of tissue deformations. To calibrate the parameters to the experimental results, we developed a three dimensional FE model to simulate the forces at the indenter and an optimization program that updates new parameters and runs the simulation iteratively. The comparison between simulation and experimental behavior of pig intra abdominal soft tissue are presented to provide a validness of the tissue model using our approach.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.582-587
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• 1997

This paper deals with the control problem under nonlinear boiler systems with noise, and input constraints. MCMBPC(Multivariable Constrained Model-Based Predictive Controller) proposed by Wilkinson et al.[10,11] is used and nominal model is modified in this paper in order to applied to nonlinear boiler systems with feed-forward terms. The solution of the cost function optimization constrained on input and/or output variables is achieved using quadratic programming, via singular value decomposition(SVD). The controller designed is shown to satisfy the constraints and to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• Journal of Korean Society for Quality Management
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• v.9 no.2
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• pp.31-36
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• 1981

This paper deals with the reliability optimization of parallel - in - series system subject to several linear constraints. The model of nonlinear constrained optimization is transformed to a saddle point problem by using Lagrange multipliers. Then Newton - Raphson method is used to solve the resulting problem and these step - by - step solution procedures are programmed in Basic Level II of micro - computer TRS-80. An example which has two linear constraints is solved and the results are analyzed.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.387-397
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• 2007

According to the controllability of pulse times and the amount of jumps in the states at these times in the process of fed-batch culture producing 1,3-propanediol, this paper proposes a terminal optimal control model, whose constraint condition is the nonlinear impulsive delay system. The existence of optimal control is discussed and an optimization algorithm which is applied to each subinternal over one cycle for this optimal control problem is constructed. Finally, the numerical simulations show that the terminal intensity of producing 1,3-propanediol has been increased obviously.