Earticle

In this study, an algorithm for control of SPD(Suspended Particles Display) on Smart Skin was proposed. The office with SPD located in Jeonju, Jeollabuk-do was modeled and simulated using TRNSYS18. Through simulation, the energy and lighting consumption of building were analyzed The two kinds of control algorithm(SPD and dimming control method for cool energy and lighting energy saving(CASE 1) and improved control method(CASE 2)) were compared. For this research, Two models(with and without SPD and dimming control) were analyzed by comparing the cooling energy and the light energy consumption was reduced 15.1%, and the lightind energy consumption was reduced by 39.2% more than the model without SPD and dimming control. But, at the improved control method(CASE 2) the cooling energy consumption was reduced of more 2.5% and lighting energy consumptions was reduced of more 18.3% than CASE 1. When using SPD and dimming control, lighting energy consumptions showed more sensitive to solar radiation than cooling energy consumptions. As the improved control method(CASE 2) showed more advantageous saving tate than SPD and dimming control metrhod for cool energy and lighting energy saving(CASE 1), it was found that the improved control method (CASE 2) must be utilized in practice for SPD and dimming control.

In this study, a smart skin system that combines SPD (suspended particle display) and LGG (Lighting Guide Glass) and its optimal control method was developed for the purpose of simultaneously reducing the lighting load and cooling load in office buildings. And a demonstration site was built to test the results. The demonstration site was constructed as an experimental group with a smart skin system installed and a control group with a general window system installed. When the cooling energy consumption of the experimental group to which the smart skin system was applied was reduced by about 36.9% compared to the control group, the lighting energy was also reduced by 54.4%.

Generally, about 67% of hydropower generation is depending on the rainy season. In other word, the process of development of water resources is too limited to a particular season. As a solution to this problem, this paper proposes an optimal control method of hydroelectric power development in multi level water dams. The main advantage of the system is stabilization of the amount of power generate in dams. Simulation results show that the proposed optimal control method indicates development rate in Chungpyung Dam is about a 40%, 25% in Chungju Dam and 37.5% in Paldang.

In energy injection resonant AC-AC converters, due to the low frequency effect of the AC input envelope and the low energy injection losses requirement, the constant and steady control of the high frequency AC output envelope is still a problem that has not been solved very well. With the aid of system modeling, this paper analyzes the mechanism of the envelope pit on the resonant AC current. The computing methods for the critical damping point, the falling time and the bottom value of the envelope pit are presented as well. Furthermore, this paper concludes the stability precondition of the system AC output. Accordingly, an optimal control method for the AC output envelope is put forward based on the envelope prediction model. This control method can predict system responses dynamically under different series of control decisions. In addition, this control method can select best series of control decisions to make the AC output envelope stable and constant. Simulation and experimental results for a contactless power transfer system verify the control method.

An optimal Stabilization technique for a bilinear in duction model is introduced. This technique includes to o parts; the one is an stabilization control using Lyap unov Function which has the form of a sum of linear and quadratic function of the state variables, and the other is an optimal control using the performance index which depends on the choice of the elements of the Ly apunov matrices concerning both the state variables and the input variables. Therefore, induction motor is drived with the shorter transient time of the state variables and with the smaller overshoot of the ones, simulation results are obtained from a digital computer. Experimental ones are obtained from implementation of the optimizing controller using 8086 microprocessor kits and analog circuits are compared.

This paper deals with determining the sufficient conditions of minimum for the class of problems in which the necessary conditions of optimum are satisfied in the strengthened form Legendre-Clebsch. To this paper, we shall use the sweep method which analysis the conditions of existence of the conjugated points on the optimal trajectory. The study we have done evaluates the command variation on the neighboring optimal trajectory. The sufficient conditions of minimum are obtained by imposing the positivity of the second variation. The results that this method offers are applied to the problem o the orbital rendez-vous for the linear case of the equations of movement.

최대치 (또는 최소치)원리의 기본개념을 써서 제어함수 u(t)를 찾는데는 2점간 경계치 문제의 해결이 요구된다. 그런데 최근에는 2점간 문제를 푸는 방법으로 초기 costate vector를 찾아 문제를 해결하는 여러 가지 편법이 개발되고 있다. 여기에서는 최적제어함수를 찾는 새로운 방법의 하나로써 Newton's Sequential 방법을 적용하였다. 그리고 일차적으로 주어진 문제의 수학적인 전개를 시도하였다. 앞으로 이 방법의 물리적인 의의와 공학적인 가치는 Computer에 의해서 여러 가지 응용문제를 해결함으로써 밝혀질 것이다.

Determination of a two-point boundary value problem is the key of finding the control function u(f) with the application of the fundamental idea of Minimum principle. The late development shows the discovery of the initial testate vector for the solution of a two-point value problem. As a new technique of determining the optimal control function, Newton's sequential method is examined in this paper.

In this article, an optimal control problem associated with convection-diffusion equation is considered. Using Lagrange multiplier, the optimality system is obtained. The derived optimal system becomes coupled, non-symmetric partial differential equations. For discretizations and implementations, the finite element multigrid V-cycle is employed. The convergence analysis of finite element multigrid methods for the derived optimal system is shown. Some numerical simulations are performed.

We consider the Newton's method for an direct solver of the optimal control problems of the Navier-Stokes equations. We show that the finite element solutions of the optimal control problem for Stoke equations may be chosen as the initial guess for the quadratic convergence of Newton's algorithm applied to the optimal control problem for the Navier-Stokes equations provided there are sufficiently small mesh size h and the moderate Reynold's number.

최대치(또는 최소치) 원리의 기본개념을 써서 제어함수 u(t)를 찾는데는 2점간 경계치 문제의 해결이 요구된다. 그런데 최근에는 2점간 문제를 푸는 방법으로 초기 costate vector를 찾아 문제를 해결하는 여러가지 편법이 개발되고 있다. 여기에서는 최적제어 함수를 찾는 새로운 방법의 하나로써 고안된 Newton's sequential방법을 써서 여러가지 공학적 문제를 풀어 봄으로써 이 방법이 매우 유효하다는 것을 알아냈다.

Determination of a two-point boundary value problem is the key of finding the control function u(t) with the application of the fundamental idea of Minimum principle. The late development shows the discovery of the initial costate vector for the solution of a two-point value problem. As a new technique of determining the optimal control function, Newton's Sequential method is examined about a number of engineering problems and found available.

This paper analyzes the $h{\times}p$ version of the finite element method for optimal control problems constrained by elliptic partial differential equations with random inputs. The main result is that the $h{\times}p$ error bound for the control problems subject to stochastic partial differential equations leads to an exponential rate of convergence with respect to p as for the corresponding direct problems. Numerical examples are used to confirm the theoretical results.

This paper presents an analytical approximate solution for a class of nonlinear quadratic optimal control problems. The proposed method consists of a Variational Iteration Method (VIM) together with a shooting method like procedure, for solving the extreme conditions obtained from the Pontryagin's Maximum Principle (PMP). This method is applicable for a large class of nonlinear quadratic optimal control problems. In order to use the proposed method, a control design algorithm with low computational complexity is presented. Through the finite iterations of algorithm, a suboptimal control law is obtained for the nonlinear optimal control problem. Two illustrative examples are given to demonstrate the simplicity and efficiency of the proposed method.

First-order least-squares method of a distributed optimal control problem for the incompressible Stokes equations is considered. An optimality system for the optimal solution are reformulated to the equivalent first-order system by introducing the vorticity and then the least-squares functional corresponding to the system is defined in terms of the sum of the squared $H^{-1}$ and $L^2$ norms of the residual equations of the system. Finite element approximations are studied and optimal error estimates are obtained. Resulting linear system of the optimality system is symmetric and positive definite. The V-cycle multigrid method is applied to the system to test computational efficiency.

This article investigates various transcription techniques for the Legendre pseudospectral (PS) method to compare the pros and cons of each approach. Eight combinations from four different types of collocation points and two discretization methods for dynamic constraints, which differentiate Legendre PS transcription techniques, are implemented to solve a carefully selected test set of nonlinear optimal control problems (NOCPs). The convergence property and prediction accuracy are compared to provide a useful guideline for selecting the best combination. The tested NOCPs consist of the minimum time, minimum energy, and problems with state and control constraints. Therefore, the results drawn from this comparative study apply to the solution of similar types of NOCPs and can mitigate much debate about the best combinations. Additionally, important findings from this study can be used to improve the numerical efficiency of the Legendre PS methods. Three PS applications to the aerospace engineering problems are demonstrated to prove this point.

Optimal control theories based on the maximum principles have been evolved and applied to distributed parameter systems(DPSs) represented by partial differential equations (PDEs) and integral equations (IEs). This paper intends to show that an optimal control of a tubular reactor described by a one-dimensional partial differential equation was obtained using the distributed parameter control method for parabolic PDEs. In develping an algorithm which implements the calculation, the method of lines (MOL) was adopted through using a package called the DSS/2. For the tubular reactor system chosen for this paper, the optimal control method based on PDEs with the numerical MOL showed to be more efficient than the one based on IEs.

Control algorithms for an absorption air conditioning system may be developed by using dynamic models of the system. The simplified effective dynamic models, which can predict the dynamic behaviors of the system, may help to develop effective control algorithms for the system. In this study, control algorithms for an absorption air conditioning system were developed by using a dynamic simulation program. A cooling water inlet temperature control algorithm, a chilled water outlet temperature control algorithm, and a supply air temperature control algorithm, were developed and analyzed. The steepest descent method was used as an optimal algorithm. Simulation results showed energy savings and the effective controls of an absorption air conditioning system.

This paper is concerned with the design of a predictive PID controller, which has similar features to the model-based predictive controller. A PID type control structure is defined which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the PID gains are pre-calculated using the values of gains calculated from an unconstrained generalized predictive control algorithm. Simulation studies demonstrate the performance of the proposed controller and the results are compared with generalized predictive controller and the results are compared with generalized predictive control solutions.

Thermoforming is one of the most versatile and economical process to produce polymer products. The drawback of thermoforming is difficult to control thickness of final products. Temperature distribution affects the thickness distribution of final products, but temperature difference between surface and center of sheet is difficult to decrease because of low thermal conductivity of ABS material. In order to decrease temperature difference between surface and center, heating profile must be expressed as exponential function form. In this study, Finite Difference Method was used to find out the coefficients of optimal heating profiles. Through investigation, the optimal results using Finite Difference Method show that temperature difference between surface and center of sheet can be remarkably minimized with satisfying Temperature of Forming Window.

This paper suggests an inverse optimal PID control design method for the trajectory tracking case of mechanical systems. Also, simple coarse/fine performance tuning laws are suggested based on the analysis for performance limitation of inverse optimal PID controller. Experimental results for a robot manipulator show the validity of our analysis for the performance tuning methods.

저자는 기존의 연구에서 대용량-비선형성을 가지는 유체의 최적화를 수행하기 위해 몇 가지 강력한 방법들을 제시한 바 있다. 즉, 최적화 과정에서 수렴성을 높이기 위해 step by step기법을 사용하였고, 또한 수렴속도를 높이기 위하여 최적화이터레이션 과정에서 얻어지는 민감도정보를 이용하여 시스템 평형방정식의 해석을 위한 좋은 초기치를 제공하는 방법과, 평형방정식을 구속조건으로 사용하는 동시기법(simultaneous technique)에서 착안하여 해석과 최적화 수렴 판정치를 조작하는 방법을 제시한 바 있다. 그러나 그들 기법은 기본적으로 유사뉴턴법에 기본을 두고 있다. 현재까지 최적화에서 SQP기법을 사용할 때는 정확한 헤시안 매트릭스의 유도가 매우 까다롭고 힘들기 때문에 유사뉴턴법을 사용하고 있는 실정이다. 그러나 3차원 문제와 같이 더욱 큰 용량의 문제를 위해서는 진정한 의미에서의 뉴턴법, 트루 뉴턴법(true Newton method)을 사용할 필요가 있다. 본 연구에서는 트루 뉴턴법을 사용하기 위해 헤시안 매트릭스의 정확치를 얻는 과정을 유도하고 이를 기본으로 트루 뉴턴법을 이용한 최적화 루틴을 만들었다. 그리고 이를 3차원 문제에 적용하여 그 효과를 검증하였다.

We have developed several methods for the optimization problem having large-scale and highly nonlinear system. First, step by step method in optimization process was employed to improve the convergence. In addition, techniques of furnishing good initial guesses for analysis using sensitivity information acquired from optimization iteration, and of manipulating analysis/optimization convergency criterion motivated from simultaneous technique were used. We applied them to flow control problem and verified their efficiency and robustness. However, they are based on quasi-Newton method that approximate the Hessian matrix using exact first derivatives. However solution of the Navier-Stokes equations are very cost, so we want to improve the efficiency of the optimization algorithm as much as possible. Thus we develop a true Newton method that uses exact Hessian matrix. And we apply that to the three-dimensional problem of flow around a sphere. This problem is certainly intractable with existing methods for optimal flow control. However, we can attack such problems with the methods that we developed previously and true Newton method.