• Journal of applied mathematics & informatics
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• 제9권2호
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• pp.717-730
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• 2002

In this paper we use measure theory to solve a wide range of the nonlinear programming problems. First, we transform a nonlinear programming problem to a classical optimal control problem with no restriction on states and controls. The new problem is modified into one consisting of the minimization of a special linear functional over a set of Radon measures; then we obtain an optimal measure corresponding to functional problem which is then approximated by a finite combination of atomic measures and the problem converted approximately to a finite-dimensional linear programming. Then by the solution of the linear programming problem we obtain the approximate optimal control and then, by the solution of the latter problem we obtain an approximate solution for the original problem. Furthermore, we obtain the path from the initial point to the admissible solution.

• Steel and Composite Structures
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• 제32권3호
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• pp.293-304
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• 2019

In the present paper, the element free Galerkin (EFG) method is developed for geometrically nonlinear analysis of deep beams considering small scale effect. To interpret the behavior of structure at the nano scale, the higher-order gradient elasticity nonlocal theory is taken into account. The radial point interpolation method with high order of continuity is used to construct the shape functions. The nonlinear equation of motion is derived using the principle of the minimization of total potential energy based on total Lagrangian approach. The Newmark method with the small time steps is used to solve the time dependent equations. At each time step, the iterative Newton-Raphson technique is applied to minimize the residential forces caused by the nonlinearity of the equations. The effects of nonlocal parameter and aspect ratio on stiffness and dynamic parameters are discussed by numerical examples. This paper furnishes a ground to develop the EFG method for large deformation analysis of structures considering small scale effects.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1838-1839
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• 2006

In this paper, a loss-minimization nonlinear torque control for Electrical Vehicle(EV) induction motors is proposed. To improve the efficiency of the induction motors, it is important to find the optimal flux reference that minimize power losses. The proposed optimal flux reference is derived using a power loss function that is constructed with stator resistance losses, rotor resistance losses and core losses. And the time-varying load torque and the rotor resistance variation are considered in the power loss function. An algorithm that identifying the load torque is used. The rotor flux observer is used to obtain an accurate flux value regardless of the rotor resistance variation. Simulation results show a significant reduction in energy losses.

• Structural Engineering and Mechanics
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• 제90권2호
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• pp.189-208
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• 2024

Artificial intelligence is one of the efficient methods that can be developed to simulate nonlinear behavior and predict the response of building structures. In this regard, an adaptive method based on optimization algorithms is used to train the TSK model of the fuzzy inference system to estimate the seismic behavior of building structures based on analytical data. The optimization algorithm is implemented to determine the parameters of the TSK model based on the minimization of prediction error for the training data set. The adaptive training is designed on the feedback of the results of previous time steps, in which three training cases of 2, 5, and 10 previous time steps were used. The training data is collected from the results of nonlinear time history analysis under 100 ground motion records with different seismic properties. Also, 10 records were used to test the inference system. The performance of the proposed inference system is evaluated on two 3 and 20-story models of nonlinear steel moment frame. The results show that the inference system of the TSK model by combining the optimization method is an efficient computational method for predicting the response of nonlinear structures. Meanwhile, the multi-vers optimization (MVO) algorithm is more accurate in determining the optimal parameters of the TSK model. Also, the accuracy of the results increases significantly with increasing the number of previous steps.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.387-392
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• 2005

Double-deck train have studied in the next generation train in KRRI. Double-deck train have more seat capacities compared with single deck vehicles and is a efficient, reliable and comfortable alternative train. Because of heavy weight, weight minimization of double-deck train carbody is imperative to reduce cost and extend life-time of train. Weight minimization problem of the double-deck train car-body is required to decide 66 design variables of thicknesses for large aluminum extruded panel while satisfying stress constraints. Design variables are too many and one execution of structural analysis of double-deck train carbody is time-consuming. Therefore, we adopt approximation technique to save computational cost of optimization process. Metamodels such as response surface model (RSM) and kriging model are used to approximate model-based optimization is described. RSM is easy to obtain and expressed explicit function, but this is not suitable for highly nonlinear and large scaled problems. Kriging model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. Target of this design is to find optimum thickness of AEP to minimize weight of doulbe-deck train carbody. In this study, meta model techniques are introduced to carry out weight minimization of a double-deck train car-body.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.478-488
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• 2014

Torque pulsation mechanism and highly nonlinear magnetic characterization of switched reluctance motors(SRM) lead to unfavorable torque ripple and limit the variety of applications in industry. In this paper, a modification method proposed for torque ripple minimization of SRM based on conventional torque sharing functions(TSF) to improve maximum speed of torque ripple-free operation considering converter limitations. Due to increasing phase inductance in outgoing phase during the commutation region, reference current tracking can be deteriorated especially when the speed increased. Moreover, phase torque production in incoming phase may not be reached to the reference value near the turn-on angle in which the incremental inductance would be dramatically decreased. Torque error for outgoing phase can cause increasing the resultant motor torque while it would be negative for incoming phase and yields reducing the motor torque. In this paper, a modification method is proposed in which phase torque tracking error for each phase under the commutation added to the other phase so that the resultant torque remained in constant level. This yields to extend constant torque region and reduce peak phase current when the speed increased. Simulation and experimental results for four phase 4 KW, 8/6 SRM validate the effectiveness of the proposed scheme.

• Smart Structures and Systems
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• 제16권6호
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• pp.1133-1145
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• 2015

A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of a nonlinear structure. In the present method an NN is used as a predictor. This NN has been trained to predict the future response of the structure to determine the control forces. These control forces are calculated by minimizing the difference between the predicted and desired responses via a numerical minimization algorithm. Since the NNPC is very time consuming and not suitable for real-time control, it is then used to train an NN controller. To consider the effectiveness of the controller on probability of damage, fragility curves are generated. The approach is validated by using simulated response of a 3 story nonlinear benchmark building excited by several historical earthquake records. The simulation results are then compared with a linear quadratic Gaussian (LQG) active controller. The results indicate that the proposed algorithm is completely effective in relative displacement reduction.

• 전기의세계
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• 제24권5호
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• pp.72-80
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• 1975

In this paper an application of the Monte Carlo method to optimum circuit design is discussed. T. Tsuda and T. Kiyono's algorithm based on the Monte Carlo method for solving multiple simul-taneous nonlinear equations is generalized to apply it to finding solutions of the constrained nonlinear optimization problem. The generalized algorithm derived here is directly applied to economical circuit design. In the cirsuit design, the object function is a cost function which is related to the cost of each circuit component. The constraint is the variance of the total system expressed by the variances of each circuit component. The design is to be determined so that the circuit has specified drift reliability with minimum cost. A practical example of economical circuit design and a general nonlinear function minimization is presented with food results.

• Transactions on Control, Automation and Systems Engineering
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• 제2권1호
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• pp.56-61
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• 2000

Majority of industrial robots are controlled by a simple independent joint control of joint actuators rather than complex controllers based on the nonlinear dynamic model of the robot manipulator. In this independent joint control scheme, the performance of actuator control is influenced significantly by the joint disturbance torques including gravity, Coriolis and centrifugal torques, which result in the trajectory tracking error in the joint control system. The control performance of a redundant manipulator under independent joint control can be improved by minimizing this joint disturbance torque in resolving the kinematic redundancy. A 3 DOF planar robot is studied as an example, and the dynamic programming method is used to find the globally optimal joint trajectory that minimize the joint disturbance torque over the entire motion. The resulting solution is compared with the solution obtained by the conventional joint torque minimization, and it is shown that joint disturbance can be reduced using the kinematic redundancy.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1996년도 춘계학술대회논문집; 부산수산대학교, 10 May 1996
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• pp.298-305
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• 1996

The common practice for the identification of piezoelectric properties is based on the use of immittance behavior of a resonator with a certain geometry and poling direction. In this paper, a new method is suggested to identify the complex-valued piezoelectric material constants. This method is based on the minimization of differences between the analytical immittance and the experimental measurement of resonator. Non-linear minimization problems are formulated to find out the unknown properties relevant to the resonators. The immittance data used for identification are measured at a number of frequencies which cover the vicinity of resonance frequency and the low frequency region. To illustrate the proposed technique, the complex-valued coefficients are identified for a typical PZT4 ceramic composition.