• 전기의세계
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• v.30 no.8
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• pp.509-516
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• 1981

The optimal control theory is applied to the design of a digital control system for a nuclear reactor. A linear dynamic model obtained at 85% of rated power and a quadratic performance index are used. A minimal order observer used in cascade with the feedback controller is suggested as a state estimator. The total reactor power control is studied in the range of 80% to 100% of rated power, with the steady state and load-following control. The control algorithm considered is suitable for implementation in direct digital control.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.28-33
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• 2015

In this paper, we propose a near optimal controller design method for permanent magnet synchronous generators (PMSGs) of MW-class direct-driven wind turbine systems based on SDRE (State Dependent Riccati Equation) approach. Using the solution matrix of an SDRE, we parameterize the optimal controller gain. We present a simple algorithm to compute the near optimal controller gain. The proposed optimal controller can enable PMSGs to precisely track the reference speed determined by the MPPT algorithm. Finally, numerical simulation results are given to verify the effectiveness of the proposed optimal controller.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.488-492
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• 1986

This paper presents a design method for PID controller using optimal control theory. The procedures of the applied method consist of (1) sampling the system response to the test signal, (2) processing the sampled data using RPE method to identify the parameters of the plant, (3) calculating the optimal value of the PID controller parameters using LQ theory. This controller is implemented on the digital computer and applied to real servomechanism, yielding satisfactory result.

• Korean Journal of Chemical Engineering
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• v.36 no.3
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• pp.356-367
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• 2019

This work presents an advanced and systematic approach to analytically design the optimal parameters of a two parameter second-order internal model control (IMC) filter that satisfies operational constraints on the output process, the manipulated variable as well as rate of change of the manipulated variable, for a first-order plus dead time (FOPDT) process. The IMC parameters are designed to minimize a control objective function composed of the weighted sum of the error between the process variable and the set point, and the rate of change of the manipulated variable, and to satisfy the desired constraints. The feasible region of the constrained IMC control parameters was graphically analyzed, as the process parameters and the constraints varied. The resulting constrained IMC control parameters were also used to find the corresponding industrial proportional-integral controller parameters of a Smith predictor structure.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.2
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• pp.76-82
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• 1984

This paper presents the design and the optimal control method of current-fed half-brige switching regulator. To achieve fast response load current variation is fed to control input, and simple optimal control model has been derived with provision of current control loop in the control circuit. Test results show that the control system model is correct and 5ms response time has been obtained at 25 KHz switching frequency.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.15-20
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• 2004

In this paper, design approach of PID controller with rejection function against external disturbance in motor control system is proposed using bacterial foraging based optimal algorithm. Up to the present time, PID Controller has been used to operate for AC motor drive because of its implementational advantages in practice and simple structure. However, it is not easy to achieve an optimal PID gain with no experience, since the gain of the PID controller has to be manually tuned by trial and error in the industrial system with disturbance. To design disturbance rejection tuning, disturbance rejection conditions based on H$\_$$\infty$/ are illustrated and the performance of response based on the bacterial foraging is computed for the designed PID controller as ITSE (Integral of time weighted squared error). Hence, parameters of PID controller are selected by bacterial foraging based optimal algorithm to obtain the required response.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.561-566
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• 1998

This paper presents an algebraic approach to optimal control for time invariant continuous system using STWS(single term Walsh series). In optimal control, it is well known that the design problem with quadratic performance criteria often involves the determination of time-varying feedback gain matrix by solving the matrix nonlinear Riccati equation and of command signal by solving the integral equation, which makes design procedure quite difficult. Therefore, in order to resolve this problem, this paper is introduced to STWS. In this paper, the time-varying feedback gains and command signals are determined by piecewise constant gains which can be easily obtained from algebraic equation using STWS.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.580-583
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• 2003

The general time optimal control law provides the optimal solution for a minimum time control problem. But in most real systems with disturbances and model uncertainties, the time optimal control law leads to chattering effect. This chattering effect can cause the system to be unstable. Therefore, we propose a robust optimal control algorithm for the nonlinear second order systems with model uncertainty. The proposed algorithm is combined with bang-bang control and sliding mode control. Thus the proposed algorithm has two state space regions to implement to control algorithm. In each region, the appropriate linear or nonlinear feedback control law is used satisfying the dynamic system equations. Simulation results show the superiority of the proposed controller in comparison with pure time optimal control(bang-bang control).

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.81-88
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• 2017

This study deals with the optimal design of a hybrid control system composed of a combination of active control system and passive control system for effective seismic performance improvement of two adjacent structures. The proposed hybrid control system adopts a configuration of installing an active control device in one building and connecting two adjacent structures with a passive control device so that the one-side active control force can be bi-directionally applied to both buildings through the passive connecting devices. In order to derive the optimal performance of the proposed system, the design parameters of the passive and active control systems were searched using the genetic algorithm. Numerical simulations of 10-story and 8-story buildings have been performed to verify the effectiveness of the proposed technique. For the purpose of comparison, the conventional independent control system with two identical active control systems being installed separately for each structure was also optimally designed and its seismic response has been evaluated as well. From the comparative results of the two control systems, it is demonstrated that the proposed hybrid control system requires larger control force for its one-side active control device than the conventional independent control system does for each of both-side active devices, but quite less than the total control force required for both-side devices of the independent control system, while maintaining similar seismic performance. Therefore, the proposed system is more economical and reliable than the conventional independent control system with two identical active devices.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.1002-1004
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• 1999

The aim of this paper is to suggest a design method of the optimal multivariable $H_{\infty}$ control system using genetic algorithm(GA). This $H_{\infty}$ control system is designed by applying GA to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H_{\infty}$ controller in the state space. The effectiveness of this $H_{\infty}$ control system is verified by nonlinear simulation.