• Proceedings of the KIEE Conference
• /
• 2003.11a
• /
• pp.220-223
• /
• 2003

This paper presents VSCOPF(Votage Stability Constrained Optimal Power Flow) algorithm based on SLP(Successive Linear Programming) to interpret the large scale system. Voltage stability index used to this paper is L index to be presented by function form. The objective function consists of load shedding cost minimization. Voltage stability indicator constraint was incorporated in traditional OPF formulation. as well as the objective function and constraints are linearlized and the optimal problem is performed by SLP(Successive Linear Programming). In this paper, the effect of voltage stability limit constraint is showed in the optimal load curtailment problems. As a result, an optimal solution is calculated to minimize load shedding cost guaranteeing voltage security level. Numerical examples using IEEE 39-bus system is also presented to illustrate the capabilities of the proposed formulation.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.1
• /
• pp.165-171
• /
• 2014

We develop an optimization algorithm for a periodic review inventory system under a stochastic budget constraint. While most conventional studies on the periodic review inventory system consider a simple budget limit in terms of the inventory investment being less than a fixed budget, this study adopts more realistic assumption in that purchasing costs are paid at the time an order is arrived. Therefore, probability is employed to express the budget constraint. That is, the probability of total inventory investment to be less than budget must be greater than a certain value assuming that purchasing costs are paid at the time an order is arrived. We express the budget constraint in terms of the Lagrange multiplier and suggest a numerical method to obtain optional values of the cycle time and the safety factor to the system. We also perform the sensitivity analysis in order to investigate the dependence of important quantities on the budget constraint. We find that, as the amount of budget increases, the cycle time and the average inventory level increase, whereas the Lagrange multiplier decreases. In addition, as budget increases, the safety factor increases and reaches to a certain level. In particular, we derive the condition for the maximum safety factor.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.468-472
• /
• 2003

The lifting technique is a standard control procedure that is commonly applied to dual-rate systems, where a critical difficulty is that care must be taken so that the resulting equivalent system preserves the causality constraint between the control signal and the measured output. To overcome this difficulty, the most attractive result has been suggested by defining control time sequences as the union of sample and hold time sequences. However, the sacrifice of regular control period scheme results in some serious disadvantages; restrictions on the implementation to hardware and the corresponding inefficient control scheme. On the contrary, this paper proposes a novel dual-rate control technique, which redescribes the system as a control-rate-based system having regular control period and designs the controller, with no causality constraint, through Linear Matrix Inequality (LMI) formulation.

• The Journal of Korean Association of Computer Education
• /
• v.8 no.1
• /
• pp.73-80
• /
• 2005

To achieve a natural and plausible interaction with deformable objects and to setup the desirable initial conditions of simulation, user should be able to define and control the geometric constraints intuitively. In addition, user should be able to utilize the simulation as a problem solving platform by experimenting various simulation situations without major modification of the simulator. The proposed physically based geometric constraint simulation system solves the problem using a non-linear finite element method approach to represent deformable objects and constraint forces are generated by defining geometric constraints on the nodes of the object to maintain the restriction. It allows user to define and modify geometric constraints and an algorithm converts these geometric constraints into constraint forces which seamlessly integrate controllability to the simulation system. Simulator can handle linear, angular, inequality based geometric constraints on the objects. Our experimental results show that constraints are maintained in the tight error bound and preserve desired shape of deformable object during the entire simulation.

• Journal of applied mathematics & informatics
• /
• v.20 no.1_2
• /
• pp.345-354
• /
• 2006

In this paper first, we find a canonical symmetrical trapezoidal(triangular) for the solution of the fuzzy linear system $A\tilde{x}=\tilde{b}$, where the elements in A and $\tilde{b}$ are crisp and arbitrary fuzzy numbers, respectively. Then, a model for fuzzy linear programming problem with fuzzy variables (FLPFV), in which, the right hand side of constraints are arbitrary numbers, and coefficients of the objective function and constraint matrix are regarded as crisp numbers, is discussed. A numerical procedure for calculating a canonical symmetrical trapezoidal representation for the solution of fuzzy linear system and the optimal solution of FLPFV, (if there exist) is proposed. Several examples illustrate these ideas.

• Transactions on Control, Automation and Systems Engineering
• /
• v.4 no.4
• /
• pp.289-295
• /
• 2002

In this paper, a linear matrix inequality(LMI)-based robust control method, which combines model predictive control(MPC) with the feedback linearization(FL), is presented for constrained nonlinear systems with parameter uncertainty. The design procedures consist of the following 3 steps: Polytopic description of nonlinear system with a parameter uncertainty via FL, Mapping of actual input constraint by FL into constraint on new input of linearized system, Optimization of the constrained MPC problem based on LMI. To verify the performance and usefulness of the control method proposed in this paper, some simulations with application to a flexible single link manipulator are performed.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.492-492
• /
• 2000

This paper proposes LQ optimal controller design method based on the modal decomposition. Here, the design problem of linear time-invariant systems is considered by using pencil model. The mathematical model based on matrix pencil is one of the most general representation of the system. By adding some conditions the model can be reduced to traditional system models. In pencil model, the state feedback is considered as an algebraic constraint between the state variable and the control input variable. The algebraic constraint on pencil model is called purely static mode, and is included in infinite mode. Therefore, the information of the constant gain controller is included in the purely static mode of the augmented system which consists of the plant and the control conditions. We pay attention to the coordinate transformation matrix, and LQ optimal controller is derived from the algebraic constraint of the internal variable. The proposed method is applied to the numerical examples, and the results are verified.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.7
• /
• pp.619-624
• /
• 2011

This paper presents a controller design method for a robust control problem with multiple constraints using genetic algorithms and LMI design method. A robust $H_{\infty}$ constraint with loop shaping and pole placement is used to address disturbance attenuation with error limits and desired transient specifications, in spite of the plant uncertainties and disturbances. In addition, a loop gain constraint is considered so as not to enlarge the loop gain unnecessarily. The robust $H_{\infty}$ constraint and pole placement constraint can be expressed in terms of two matrix inequalities and the loop gain constraint can be considered as an objective function so that genetic algorithms can be applied. Accordingly, a robust controller can be obtained by integrating genetic algorithms with LMI approach. The proposed controller design method is applied to a track-following system of an optical disk drive and is evaluated through simulation results.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.11a
• /
• pp.660-664
• /
• 2003

The optimal thickness distribution of an active damping layer is sought so that it satisfies a certain constraint on the dynamic performance of a system minimizing control efforts. To obtain a topologically optimized configuration, which includes size and shape optimization, thickness of the active damping layer is interpolated using linear functions. With the control energy as the objective function to be minimized, the state error energy is introduced as the dynamic performance criterion for the system and used lot a constraint. The optimal control gains are evaluated from LQR simultaneously as the optimization of the layer position proceeds. From numerical simulation, the topologically optimized distribution of the active damping layer shows the same dynamic performance and cost as the Idly covered counterpart, which is optimized only in terms of control gains, with less amount of the layer.

• Journal of the Korean Statistical Society
• /
• v.4 no.1
• /
• pp.67-78
• /
• 1975

Over twenty-five years ago, Professor Klein and Rubin presented the linear expenditure system. That system was first estimated by Stone. Subsequently many investigators have estimated that system. In this paper, many points of the error structure shown by Pollak and Wales are referred to. Barten presented an estimation theorem on a singular covariance matrix. In order to estimate parameters, we place an emphasis on the maximum likihood method which we believe to be most appropriate. As we have one linear restriction on parameters to be estimated, we maximized the associated likelihood function subject to that linear restriction through the well-known lagrange multiplier method. This paper is organized in the following fashion : (1) a brief description on classical consumer theory, (2) a linear expenditure system and its constraint, (3) dyanmic specification and stochastic specification, (4) estimation method, and (5) conclusion.