• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2617-2622
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• 2003

The pH neutralization process has long been taken as a representative benchmark problem of nonlinear chemical process control due to its nonlinearity and time-varying nature. For general nonlinear processes, it is difficult to control with a linear model-based control method so nonlinear controls must be considered. Among the numerous approaches suggested, the most rigorous approach is the dynamic optimization. However, as the size of the problem grows, the dynamic programming approach is suffered from the curse of dimensionality. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach was proposed by Bertsekas and Tsitsiklis (1996). The NDP approach is to utilize all the data collected to generate an approximation of optimal cost-to-go function which was used to find the optimal input movement in real time control. The approximation could be any type of function such as polynomials, neural networks and etc. In this study, an algorithm using NDP approach was applied to a pH neutralization process to investigate the feasibility of the NDP algorithm and to deepen the understanding of the basic characteristics of this algorithm. As the global approximator, the neural network which requires training and k-nearest neighbor method which requires querying instead of training are investigated. The global approximator requires optimal control strategy. If the optimal control strategy is not available, suboptimal control strategy can be used even though the laborious Bellman iterations are necessary. For pH neutralization process it is rather easy to devise an optimal control strategy. Thus, we used an optimal control strategy and did not perform the Bellman iteration. Also, the effects of constraints on control moves are studied. From the simulations, the NDP method outperforms the conventional PID control.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.5
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• pp.543-551
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• 2011

The paper deals with the comparative study of design optimization based on various approximation techniques in strength design of riser support structure installed on floating production storage and offloading unit(FPSO) using offshore operation loading conditions. The design optimization problem is formulated such that structural member sizing variables are determined by minimizing the weight of riser support structure subject to the constraints of structural strength in terms of loading conditions. The approximation techniques used in the comparative study are response surface method based sequential approximate optimization(RBSAO), Kriging based sequential approximate optimization(KBSAO), and the enhanced moving least squares method(MLSM) based approximate optimization such as CF(constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization(PIDO) tools are employed for the applications of RBSAO and KBSAO. The enhanced MLSM based approximate optimization techniques are newly developed to ensure the constraint feasibility. In the context of numerical performances such as design solution and computational cost, the solution results from approximate techniques based design optimization are compared to actual non-approximate design optimization.

• Journal of The Korean Astronomical Society
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• v.14 no.1
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• pp.37-42
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• 1981

In order to know how the magnetic field increases with density in interstellar clouds, we have analyzed observations of extinction and polarization for stars in the ${\rho}$ Oph molecular cloud complex. The size of grains in dense parts of the complex is estimated to be larger than the ones in diffuse interstellar clouds by about 15 percent in radii. Employing the Davis-Greenstein mechanism for grain alignment with this estimated grain size, we have put constraints on the exponent in the field-density relation $B{\propto}n^x:1/5{\leq}x{\leq}1/3$. It is concluded that magnetic field in gravitationally contracting clouds increases less steeply than the classical expectation based on the approximation of isotropic contraction with complete frozen-in flux.

• Tunnel and Underground Space
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• v.20 no.3
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• pp.153-168
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• 2010

A fifth equation is required to determine the five independent elastic constants of a transversely isotropic rock from compression test of a single specimen. As an approximation proposed by Saint-Venant has been used for long time, it may cause an erroneous result in some cases, especially for specimen with low angle of anisotropy. Three equations were suggested replacing this traditional equation and proved to be applicable by the model analysis in the previous studies. As Saint-Venant's approximation is turned out the same as the first one of them, it has the characteristics that the apparent Young's modulus is monotonously increasing according to the anisotropic angle. The methodology to analyze the elastic constants from four independent strain measurements by uniaxial compressive test of a single standard specimen is concisely described, and the necessity and compatibility of new suggested equations are discussed. Saint-Venant's approximation can determine the elastic constants close to true values and other equations may be unnecessary in specimens with medium to large angle. Nevertheless, they may become applicable because they can produce the almost same amount. For the specimens of small angle of anisotropy, Saint-Venant's approximation may result in out of general ranges or thermodynamic constraints, but other suggested equations can produce the almost true value. Thus they can be applied before other alternative equation is known. The guide map constructed by model study may decide the most compatible one of the three equations.

• Proceedings of the Korea Water Resources Association Conference
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• 1983.07a
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• pp.78-79
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• 1983

It is well known that small amplitude wave theory, a first approximation to the complete theoretical description of wave behavior, yields a maximum investment in mathematical endeavor. But, if the wave amplitude is large, the small amplitude considerations are not valid, and finite amplitude wave theory which retains higher-order terms to obtain an accurate representation of the wave motion is numercal theory. The Stream function wave theory, one of the numerical methods, was developed by Dean for use with asymmetric measured wave profiles and with symmetric theoretical wave profiles. Dalrymple later improved the comjputational procedure by adding two Lagrangian constraints so that more efficient convergence of the iterative numerical method to a specified wave heigh and to a zero mean free surface displacement resulted. This paper introduces in details the Dean and Darlymple Stream Function Method in case of the symmetric theoretical wave, because in design purposes, wave height and wave period are given.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.530-533
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• 1995

This paper deals with the problem of motion planning for a unicycle-like robot. We present a simple local planner for unicycle model, based on an approximation of the desired configuration generated by local holonomic planner that ignores motion constraints. To guarantee a collision avoidance, we propose an inequality constraint, based on the motion analysis with the constant control input and time interval. Consequently, we formulate our problem as the constrained optimization problem and a feedback scheme based on local sensor information is established by simply solving this problem. Through simulations, we confirm the validity and effectiveness of our algorithm.

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.425-429
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• 1987

This paper describes a collision avoidance method for planning safe trajectories for multi-robot system in common work space. Usually objects have been approximated to convex polyhedra in most previous researches, but in case using such the approximation method it is difficult to represent objects analytically in terms of functions and also to describe tile relationship between the objects. In this paper, in order to solve such problems a modeling method which approximates objects to cylinder ended by hemispheres and or sphere is used and the maximum distance functions is defined which call be calculated simply. Using an objective function with inequality constraints which are related to minimum distance functions, work range and maximum allowable angular velocities of the robots, tile collision avoidance for two robots is formulated to a constrained function optimization problem. With a view to solve tile problem a penalty function having simple form is defined and used. A simple numerical example involving two PUMA-type robots is described.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.4
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• pp.27-36
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• 1996

It is well known that the viterbi algorithm proposed as a mthod of decoding convolutional codes is in fact maximum likelihood (ML) and therefore optimal. But, because hardware complexity grows exponentially with the constraint length, there will be severe constraints on the implementation of the viterbi decoders. In this paper, the three-layered backpropagation neural networks are proposed as an alternative in order to get sufficiently useful performance and deal successfully with the problems of the viterbi decoder. This paper shows that the neural convolutional decoder (NCD) can make a decision in the point of ML in decoding and describes simulation results. The cause of the difference between stochastic results and simulation results is discussed, and then thefuture prospect of the NCD is described on the basis of the characteristic of the transfer function.

• Journal of applied mathematics & informatics
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• v.32 no.5_6
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• pp.707-719
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• 2014

In this paper, we investigate a variational discretization approximation of elliptic optimal control problems with control constraints. The state and the co-state are approximated by piecewise linear functions, while the control is not directly discretized. By using some proper intermediate variables, we derive a second-order convergence in $L^2$-norm and superconvergence between the numerical solution and elliptic projection of the exact solution in $H^1$-norm or the gradient of the exact solution and recovery gradient in $L^2$-norm. Then we construct a posteriori error estimates by using the superconvergence results and do some numerical experiments to confirm our theoretical results.

• Structural Engineering and Mechanics
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• v.62 no.3
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• pp.303-310
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• 2017

The model updating problems, which are to find the optimal approximation to the discrete quadratic model obtained by the finite element method, are critically important to the vibration analysis. In this paper, the structured model updating problem is considered, where the coefficient matrices are required to be symmetric and positive semidefinite, represent the interconnectivity of elements in the physical configuration and minimize the dynamics equations, and furthermore, due to the physical feasibility, the physical parameters should be positive. To the best of our knowledge, the model updating problem involving all these constraints has not been proposed in the existed literature. In this paper, based on the semidefinite programming technique, we design a general-purpose numerical algorithm for solving the structured model updating problems with incomplete measured data and present some numerical results to demonstrate the effectiveness of our method.