• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.95-98
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• 2003

In this paper, an adaptive fuzzy neural control of unknown nonlinear systems based on the rapid learning algorithm is proposed for optimal parameterization. We combine the advantages of fuzzy control and neural network techniques to develop an adaptive fuzzy control system for updating nonlinear parameters of controller. The Fuzzy Neural Network(FNN), which is constructed by an equivalent four-layer connectionist network, is able to learn to control a process by updating the membership functions. The free parameters of the AFN controller are adjusted on-line according to the control law and adaptive law for the purpose of controlling the plant track a given trajectory and it's initial values are off-line preprocessing, In order to improve the convergence of the learning process, we propose a rapid learning algorithm which combines the error back-propagation algorithm with Aitken's $\delta$$\^$2/ algorithm. The heart of this approach ls to reduce the computational burden during the FNN learning process and to improve convergence speed. The simulation results for nonlinear plant demonstrate the control effectiveness of the proposed system for optimal parameterization.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.8
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• pp.779-785
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• 2009

This paper is concerned with a computational approach for topology optimization of geometrically nonlinear structures following specific load-displacement trajectories. In our previous works, attention was paid to stabilize topology optimization involving large displacement and a method called the element connectivity parameterization was developed. Here, we aimed to extend the element connectivity parameterization method to find an optimal geometrically nonlinear structure yielding a specific load-displacement trajectory. In contrast to designing a stiffest structure, the trajectory design problem requires special consideration in topology optimization formulation and solution procedure. Some numerical problems were considered to test the developed element connectivity parameterization based formulation.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.1017-1022
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• 2004

Though the standard element density-based topology optimization method has been applied for the optimal design of multiphysics systems, some theoretical problems, such as material interpolation, undershoot temperature prediction, and unstable elements, still remain to be overcome. The objective of this investigation is to present a new topology optimization formulation based on the element connectivity parameterization (ECP) in order to avoid the numerical problems in multiphysics system design and improve optimization results. To show the validity of the proposed approach, the designs of an optimal thermal dissipation and an electro-thermal-compliant actuator were considered.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.146-148
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• 1998

For the shape design of electromagnetic devices using the FEM, the choice of design parameters influence to the success of the optimization process. If the design parameter distribution has a one to one corespondence with finite element model, we can encounter not only serious accuracy problem but also obtain a zigzag shape along the interface. The nodes between those design parameters can be parameterized by interpolating using one among many interpolation methods. The conventional parameterization of design parameters has a limit of application for shape, because design parameters and movable nodes are linearly intepolated. In this paper, using the B-spline curve that use to present any interfaces in computer graphics, the curvilinear parameterization between design parameters and node points is compared with the linear parameterization.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.754-759
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• 1992

In this paper, we proposed a mixed H$_{2}$/H$_{\infty}$ optimal controller design method using the parameterization of H$_{2}$ suboptimal controller. The method is based on the minimization of H$_{2}$ performance measure with an H$_{\infty}$-norm constraint. We also derived the necessary and sufficient conditions for existence of solution from the decoupled Riccati equations. And the designed controller has state-space representation.n.

• Structural Engineering and Mechanics
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• v.24 no.2
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• pp.155-180
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• 2006

Many applications in mechanical design involve elastic bodies coming into contact under the action of the applied load. The distribution of the contact pressure throughout the contact interface plays an important role in the performance of the contact system. In many applications, it is desirable to minimize the maximum contact pressure or to have an approximately uniform contact pressure distribution. Such requirements can be attained through a proper design of the initial surfaces of the contacting bodies. This problem involves a combination of two disciplines, contact mechanics and shape optimization. Therefore, the objective of the present paper is to develop an integrated procedure capable of evaluating the optimal shape of contacting bodies. The adaptive incremental convex programming method is adopted to solve the contact problem, while the augmented Lagrange multiplier method is used to control the shape optimization procedure. Further, to accommodate the manufacturing requirements, surface parameterization is considered. The proposed procedure is applied to a couple of problems, with different geometry and boundary conditions, to demonstrate the efficiency and versatility of the proposed procedure.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.240-245
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• 2005

In this paper, planar waypoint guidance synthesis for UAVs using the LQ optimal impact-angle-control guidance law is proposed. We prove that the energy-optimal control problem with the constraint of passing through the waypoints is equivalent to the problem of finding the optimal pass angles on each waypoint of the optimal impact-angle-control law. The optimal pass angles can be obtained as a numerical solution of the simple pass angle optimization problem that requires neither input parameterization nor constraints. The trajectory obtained by applying the optimal impact-angle-control law with these optimal pass angles becomes energy optimal.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.38-44
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• 1994

Control Algorithms of the Auto-Pilot system have been studied for the navigational economics and crew's comfortability since 1960's, when Auto-Pilot system was installed on the trans-ocean ships. At the beginning the PD control algorithm was used with the weather adjust function introduced to reduce the response of the auto-pilot system to the high frequency wave excitation in rough sea. In this study, the optimal and adaptive control theories are applied for the auto-pilot control algorithm. And those two algorithms are compared through the pre-defined cost function to obtain the most effective control technique for the Auto-Pilot system. The parameterization of the ship meneuvering equation for the adaptive control algorithm design procedure was examined and the advantage of the adaptive control was found through the simulation result with the wrong initial parameter value.

• Advances in aircraft and spacecraft science
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• v.6 no.5
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• pp.391-407
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• 2019

Flight trajectory optimization has become an important factor not only to reduce the operational costs (e.g.,, fuel and time related costs) of the airliners but also to reduce the environmental impact (e.g.,, emissions, contrails and noise etc.) caused by the airliners. So far, these factors have been dealt with in the context of 2D and 3D trajectory optimization, which are no longer efficient. Presently, the 4D trajectory optimization is required in order to cope with the current air traffic management (ATM). This study deals with a cubic spline approximation method for solving 4D trajectory optimization problem (TOP). The state vector, its time derivative and control vector are parameterized using cubic spline interpolation (CSI). Consequently, the objective function and constraints are expressed as functions of the value of state and control at the temporal nodes, this representation transforms the TOP into nonlinear programming problem (NLP). The proposed method is successfully applied to the generation of a minimum length optimal trajectories along 4D waypoints, where the method generated smooth 4D optimal trajectories with very accurate results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.33
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• pp.111-118
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• 1995

This paper suggests a hybrid genetic algorithm for asymmetric traveling salesman problem(TSP). The TSP was proved to be NP-complete, so it is difficult to find optimal solution in reasonable time. Therefore it is important to develope an algorithm satisfying robustness. The algorithm applies dynamic programming to find initial solution. The genetic operator is uniform order crossover and scramble sublist mutation. And experiment of parameterization has been performed.