• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.47-54
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• 2000

This article is concerned with the algorithm for the Chebyshev estimation with/without linear equality and/or inequality constraints. The algorithm employs a linear scaling transformation scheme to reduce the computational burden which is induced when the data set is quite large. The convergence of the proposed algorithm is proved. And the updating and orthogonal decomposition techniques are considered to improve the computational efficiency and numerical stability.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.3
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• pp.313-319
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• 2002

Since the oil crisis in 1970, a great deal of effort has been made to develop automatic electric load sharing systems as a part of the efforts to save energy. A large scale electric generating system composes more than two generators whose characteristics may be different. When such a system is operated individually or in parallel, the lagrange multiplier's method has difficulty in achieving optimal load distribution because generators usually have the limitations of the operating range with inequality constraints. Therefore, a suitable operating mode of generators has to be decided according to the selection of the generators to meet electric power requirements at the minimum cost. In this study, a method which solves the optimal electric load distribution problem using the dynamic programming technique is proposed. This study also shows that the dynamic programming method has an advantage in dealing with the optimal load distribution problem under the limitations of the operating range with inequality constraints including generator operation mode. In this study, generator operating cost curve of second order equation by shop trial test results of diesel generators are used. The results indicate that the proposed method can be applied to the ship's electric generating system.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.8
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• pp.71-77
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• 2002

We consider the simultaneous slewing and vibration suppression control problem of an idealized structural model which has a rigid hub with two cantilevered flexible appendages and finite tip masses. The finite clement method(FEM) is used to obtain linear finite dimensional equations of motion for the model. In the linear quadratic regulator(LQR) problem, a simple method is introduced to provide a physically meaningful performance index for space structure models. This method gives us a mathematically minor but physically important modification of the usual energy type performance index. A numerical procedure to solve a time-variant LQR problem with inequality control constraints is presented using the method of particular solutions.

• International Journal of Control, Automation, and Systems
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• v.3 no.3
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• pp.397-402
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• 2005

The guaranteed cost control problem for a class of linear systems with norm-bounded time-varying parameter uncertainties and input constraints is considered. A sufficient condition for the existence of guaranteed cost state feedback controllers is derived via the linear matrix inequality (LMI) approach, and a design procedure to guaranteed cost controllers is given. Furthermore, a convex optimization problem is formulated to determine the optimal guaranteed cost controller. An example is given to illustrate the effectiveness of the proposed results.

• Journal of the Korean Statistical Society
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• v.29 no.3
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• pp.361-373
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• 2000

A simple and efficient algorithm is introduced for generalized least squares estimation under nonnegativity constraints in the components of the parameter vector. This algorithm gives the exact solution to the estimation problem within a finite number of pivot operations. Besides an illustrative example, an empirical study is conducted for investigating the performance of the proposed algorithm. This study indicates that most of problems are solved in a few iterations, and the number of iterations required for optimal solution increases linearly to the size of the problem. Finally, we will discuss the applicability of the proposed algorithm extensively to the estimation problem having a more general set of linear inequality constraints.

• Journal of Ocean Engineering and Technology
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• v.28 no.6
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• pp.560-565
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• 2014

In this study, the problem of trajectory optimization for underwater gliders considering depth constraints is discussed. Typically, underwater gliders are controlled to dive and climb in a saw-tooth pattern at constant gliding angles. This approach is effective and close to optimal for deep water applications. However, the optimal path deviates from the saw-tooth path in shallow water conditions. This study focuses on finding more efficient gliding paths that can minimize the traverse time in the horizontal plane when the water depth is limited. The trajectory optimization problem is formulated into a minimum time control problem with inequality path constraints and hydrodynamic drag effects. A numerical approach based on the pseudo-spectral method is adopted as a solution approach, and the simulation results are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.592-599
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• 1998

In this paper, we design a tracking controller which satisfies transient response specifications and maintains tracking error within a tolerable limit for the uncertain track-following system of an optical disk drive. To this end, a robust $H_{\infty}$ control problem with regional stability constraints and sinusoidal disturbance rejection is considered. The internal model principle is used for rejecting the sinusoidal disturbance caused by eccentric rotation of the disk. We show that a condition satisfying the regional stability constraints can be expressed in terms of a linear matrix inequality (LMI) using the Lyapunov theory and S-procedure. Finally, a tracking controller is obtained by solving an LMI optimization problem involving two linear matrix inequalities. The proposed controller design method is evaluated through an experiment.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.406-410
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• 2001

This paper develops an efficient evolutionary programming based algorithm for solving the environmentally constrained economic dispatch problem in thermal power system. The proposed algorithm can deal with the power balance constraints and the emission constraints which are equality and inequality constraints, respectively. Numerical results show that the proposed algorithm can provide superior solutions within reasonable time through its application to a test system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.34.1-34
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• 2001

We deal with robust control problem for singularly perturbed linear systems with norm-bounded structured uncertainty under state constraints. We assume that the norm-bounded uncertainty is composed of repeated scalar-block and full-block forms. In the structured uncertainty, repeated scalar block forms account for uncertain physical parameter value and full-block forms may be some unknown nonlinear dynamics. In order deal with uncertainty and state constraints, we use LMI(Linear Matrix Inequality). The original problem is decomposed into two well behaved reduced order problems. Shinc two LMI problems are completely independent, each solution can be computed simultaneously and work in parallel.

• Journal of the Korean Society of Safety
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• v.30 no.3
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• pp.32-37
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• 2015

In the fields of plant layout optimization, the main goal is to minimize the construction cost including pipelines as satisfying all constraints such as safety and operating issues. However, what is the lacking of considerations in previous researches is to consider proper safety and maintenance spaces for a complex plant. Based on the mathematical programming, MILP(Mixed Integer Linear Programming) problems including various constraints can be formulated to find the optimal solution which is to achieve the best economic benefits. The objective function of this problem is the sum of piping cost, pumping cost and area cost. In general, many conventional optimization solvers are used to find a MILP problem. However, it is really hard to solve this problem due to complex inequality and equality constraints, since it is impossible to use the derivatives of objective functions and constraints. To resolve this problem, the PSO (Particle Swarm Optimization), which is one of the representative sampling approaches and does not need to use derivatives of equations, is employed to find the optimal solution considering various complex constraints in this study. The EO (Ethylene Oxide) plant is tested to verify the efficacy of the proposed method.