• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.1
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• pp.44-54
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• 2023

In this study, the second-order Nomoto's nonlinear expansion model was implemented as a Tagaki-Sugeno fuzzy model based on the heading angular velocity to design the automatic steering system of a ship considering nonlinear elements. A Tagaki-Sugeno fuzzy PID controller was designed using the applied fuzzy membership functions from the Tagaki-Sugeno fuzzy model. The linear models and fuzzy membership functions of each operating point of a given nonlinear expansion model were simultaneously tuned using a genetic algorithm. It was confirmed that the implemented Tagaki-Sugeno fuzzy model could accurately describe the given nonlinear expansion model through the Zig-Zag experiment. The optimal parameters of the sub-PID controller for each operating point of the Tagaki-Sugeno fuzzy model were searched using a genetic algorithm. The evaluation function for searching the optimal parameters considered the route extension due to course deviation and the resistance component of the ship by steering. By adding a penalty function to the evaluation function, the performance of the automatic steering system of the ship could be evaluated to track the set course without overshooting when changing the course. It was confirmed that the sub-PID controller for each operating point followed the set course to minimize the evaluation function without overshoot when changing the course. The outputs of the tuned sub-PID controllers were combined in a weighted average method using the membership functions of the Tagaki-Sugeno fuzzy model. The proposed Tagaki-Sugeno fuzzy PID controller was applied to the second-order Nomoto's nonlinear expansion model. As a result of examining the transient response characteristics for the set course change, it was confirmed that the set course tracking was satisfactorily performed.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.178-187
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• 1999

In order to identify a transfer function model with noise, penalty function method has been widely used. In this method, estimation process for possible model parameters from low to higher order proceeds the model identification process. In this study, based on linear estimation method, a new approach unifying the estimation and the identification of ARMAX model is proposed. For the parameter estimation of a transfer function model with noise, linear estimation method by noise separation is suggested instead of nonlinear estimation method. The feasibility of the proposed model identification and estimation method is verified through simulations, namely by applying the method to time series model. In the case of time series model with noise, the proposed method successfully identifies the transfer function model with noise without going through model parameter identification process in advance. A new algorithm effectively achieving model identification and parameter estimation in unified frame has been proposed. This approach is different from the conventional method used for identification of ARMAX model which needs separate parameter estimation and model identification processes. The consistency and the accuracy of the proposed method has been verified through simulations.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.8
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• pp.79-86
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• 2001

A method for actively minimizing dynamic reaction forces in a flexible structure subject to persistent excitations is presented. One difficulty with the method, however, is that forces and moments do not converge as quickly as displacements in mathematical discretization of continuous systems, so a controller based on a truncated model of a continuous system can produce poor results. A technique using residual flexibility matrix is presented for correcting the truncated force representation. A controller designed for reaction force minimization, using the residual flexibility matrix, is applied to a model of a flexible structure, and the results are presented. Implications of various reaction force penalty combinations on the resulting control performance are also discussed.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.226-228
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• 2007

This paper proposes Nonlinear Interior Point Method (NIPM) including discrete control variables optimal power flow formulations. The algorithm utilizes the robustness in terms of starting point and fast convergence for large scale power system of NIPM and an introduction of rounding penalty function which is augmented in the Lagrangian function to handle discrete control variables. The derived formulation shows a simplified approach to deal with discrete control problems which is implementable in real large scale systems.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.76-85
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• 2016

This paper presents a method of decision on where bus splitting is needed to reduce fault current level of power systems and to satisfy the fault current constraints. The method employs a modified fault current constrained optimal power flow (FCC-OPF) with X variables for the candidate locations of splitting and for decision making on whether to split or not, it adopts soft-discretization by augmenting inversed U-shaped penalty terms. Also, this paper discusses the procedure on the adequate selection of bus splitting locations based on the results of the modified FCC-OPF, to reduce the total number of the actions taken.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.551-556
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• 2001

The filling pattern technique based on the finite element method and Eulerian mesh advancement approach has been developed to analyze incompressible transient viscous flow with free surfaces. The governing equation for flow analysis is Navier-Stokes equation including inertia and gravity effects. The penalty and predictor-corrector methods are used effectively for finite element formulation. The flow front surface and the volume inflow rate are calculated using the filling pattern technique to select an adequate pattern among four filling patterns at each triangular control volume. Using the proposed numerical technique, the collapse of a dam has been analyzed to predict flow phenomenon of fluid and the predicted front positions versus time have been compared with the reported experimental result.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.174-176
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• 1997

This paper proposes a unit commitment scheduling method based on hybrid genetic algorithm(GA). When the systems are scaled up, conventional genetic algorithms suffer from computational time limitations because of the growth of the search space. So greatly reduce the search space of the GA and to efficiently deal with the constraints of the problem, priority list unit ordering scheme are incorporated as the initial solution and the minimum up and down time constraints of the units are included. The violations of other constraints are handled by integrating penalty factors. To show the effectiveness of the proposed method. test results for system of 10 units is compared with results obtained using other methods.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1346-1351
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• 2003

There is few research about contact problem in SPH because it is primarily suitable to analyze the large deformation problem. However, an elasto-plastic problem with small deformation need to be considered about contact characteristics. The numerical formulating methods for SPH is induced to be able to obtain solutions based on a variational method in contact problem. The contact algorithm presented is applied to the elastic impact problem in 1D and 2D. The results show thai an imaginary tension and a numerical instability which happen in impacting between different materials can be removed and contact forces which could not have been calculated are able to obtain.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.484-484
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• 2000

The problem of determining the proper size of an neural network is recognized to be crucial, especially for its practical implications in such important issues as learning and generalization. Unfortunately, it usually is not obvious what size is best: a system that is too snail will not be able to learn the data while one that is just big enough may learn the slowly and be very sensitive to initial conditions and learning parameters. One popular technique is commonly known as pruning and consists of training a larger than necessary network and then removing unnecessary weights/nodes. In this paper, a new pruning method is developed, based on the penalty-term methods. This method makes the neural network good for the generalization and reduces the retraining time after pruning weights/nodes.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.04a
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• pp.54-61
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• 1996

This paper deals with finite element analysis for incompressible viscous flow problem By formulating the governing equation based on the streamline upwind concept , the wiggle phenomenon of fluid flow is minimized in spite of a few number of finite element used. The penalty function method which can reduce the number of independent variables is adopted for the purpose of computational efficiency and the selected reduced integral is carried out for the convection and pressure terms to reserve the stability of solution. In time-history analysis of fluid flow, the accuracy and reliability of an obtained solution are established by using the predictor-corrector method. Finally, correlation studies between analytical and experimental results are conducted wi th the object ive to establish the validity of the proposed numerical approach.