• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.10
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• pp.1075-1085
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• 1990

This paper presents a new method for the optimal control of the distributed parameter systems by a decentralized computational procedure. Approximate lumped parameter models are derived by using the Galerkin method employing the Legendre polynomials as the basis functions. The distributed parameter systems, however, are transformed into the large scale lumped parameter models. And thus, the decentralized control scheme is introduced to determine the optimal control inputs for the obtained lumped parameter models. In addition, an approach to block pulse functions is applied to solve the optimal control problems of the obtained lumped parameter models. The proposed method is simple and efficient in computation for the optimal control of distributed paramter systems. Illustrative examples given to demonstrate the validity of the presently proposed method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.10
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• pp.464-472
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• 2001

This study uses distributed parameter systems as the spatial discretization technique, modelling in lumped parameter systems, and applies fast WALSH transform and the Picard's iteration method to high order partial differential equations and matrix partial differential equations. This thesis presents a new algorithm which usefully exercises the optimal control in the distributed parameter systems. In exercising optimal control of distributed parameter systems, excellent consequences are found without using the existing decentralized control or hierarchical control method. This study will help apply to linear time-varying systems and non-linear systems. Further research on algorithm will be required to solve the problems of convergence in case of numerous applicable intervals.

• 전기의세계
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• v.19 no.2
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• pp.21-23
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• 1970

Necessary conditions of optimal distributed parameter control systems, Hamiltons coanonical equations, welerstress condition, transversality condition and boundary condition are obtained, when the control function is constrained and the performance index takes on the general form. Also it is concluded that the lumped parameter system is the special case of the distributed parameter system.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1066-1070
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• 1990

This paper presents a method for the optimal control of the distributed parameter systems (DPSs) by a hierarehical computational procedure. Approximate lumped parameter systems (LPSs) are derived by using the Galerkin method employing the Legendre polynomials as the basis functions. The DPSs however, are transformed into the large scale LPSs. And thus, the hierarchical control scheme is introduced to determine the optimal control inputs for the obtained LPSs. In addition, an approach to block pulse functions is applied to solve the optimal control problems of the obtained LPSs. The proposed method is simple and efficient in computation for the optimal control of DPSs.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.295-298
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• 1996

In this paper, a self-tuning optimal control algorithm is proposed to retain the optimal performance of an active suspension system, when the vehicle has some time varying parameters and parameter uncertainties. We consider a 2 DOF time-varying quarter car model which has the parameter variation of sprung mass, suspension spring constant and suspension damping constant. Instead of solving algebraic riccati equation on line, we propose a neural network approach as an alternative. The optimal feedback gains obtained from the off line computation, according to parameter variations, are used as the neural network training data. When the active suspension system is on, the parameters are identified by the recursive least square method and the trained neural network controller designer finds the proper optimal feedback gains. The simulation results are represented and discussed.

• Journal of Korean Association for Spatial Structures
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• v.17 no.4
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• pp.123-132
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• 2017

A smart tuned mass damper (TMD) was developed to provide better control performance than a passive TMD for reduction of earthquake induced-responses. Because a passive TMD was developed decades ago, optimal design methods for structural parameters of a TMD, such as damping constant and stiffness, have been developed already. However, studies of optimal design method for structural parameters of a smart TMD were little performed to date. Therefore, parameter studies of structural properties of a smart TMD were conducted in this paper to develop optimal design method of a smart TMD under seismic excitation. A retractable-roof spatial structure was used as an example structure. Because dynamic characteristics of a retractable-roof spatial structure is changed based on opened or closed roof condition, control performance of smart TMD under off-tuning was investigated. Because mass ratio of TMD and smart TMD mainly affect control performance, variation of control performance due to mass ratio was investigated. Parameter studies of structural properties of a smart TMD was performed to find optimal damping constant and stiffness and it was compared with the results of optimal passive TMD design method. The design process developed in this study is expected to be used for preliminary design of a smart TMD for a retractable-roof spatial structure.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.312-315
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• 1993

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.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.411-418
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• 2006

There are mainly two types of bang-bang controllers for nominal linear time-invariant (LTI) system. Optimal bang-bang controller is designed based on optimal control theory and suboptimal bang-bang controller is obtained by using Lyapunov stability condition. In this paper, the suboptimal bang-bang control method is extended to LTI system involving both control input saturation and structured real parameter uncertainties by using Lyapunov robust stability condition. Two robust optimal bang-bang controllers are derived by minimizing the time derivative of Lyapunov function subjected to the limit of control input. The one is developed based on the classical quadratic stability(QS), and the other is developed based on the affine quadratic stability(AQS). And characteristics of the two controllers are compared. Especially, bounds of parameter uncertainties which theoretically guarantee robust stability of the two controllers are compared quantitatively for 1DOF vibrating system. Moreover, the validity of robust optimal bang-bang controller based on the AQS is shown through numerical simulations for this system.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.8
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• pp.792-804
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• 1990

This paper describes an efficient optimization algorithm by calculating sensitivity function for power system stabilization. In power system, the dynamic performance of exciter, governor etc. following a disturbance can be presented by a nonlinear differential equation. Since a nonlinear equation can be linearized for small disturbances, the state equation is expressed by a system matrix with system parameters. The objective function for power system operation will be related to the system parameter and the initial state at the optimal control condition for control or stabilization. The object function sensitivity to the system parameter can be considered to be effective in selecting the optimal parameter of the system.

• Journal of the Korean Mathematical Society
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• v.41 no.5
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• pp.821-864
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• 2004

Both parametric and parameter-free necessary and sufficient optimality conditions are established for a class of nondiffer-entiable nonconvex optimal control problems with generalized fractional objective functions, linear dynamics, and nonlinear inequality constraints on both the state and control variables. Based on these optimality results, ten Wolfe-type parametric and parameter-free duality models are formulated and weak, strong, and strict converse duality theorems are proved. These duality results contain, as special cases, similar results for minmax fractional optimal control problems involving square roots of positive semi definite quadratic forms, and for optimal control problems with fractional, discrete max, and conventional objective functions, which are particular cases of the main problem considered in this paper. The duality models presented here contain various extensions of a number of existing duality formulations for convex control problems, and subsume continuous-time generalizations of a great variety of similar dual problems investigated previously in the area of finite-dimensional nonlinear programming.