• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.51-53
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• 1993

This paper proposes a design of the tracking controller using artificial neural network and the compare the result with a result of optimal controller. In practical use, conventional Optimal controller has some limits. First, optimal controller can be designed only for linear system. Second, for many systems state observation is difficult or sometimes impossible. But the controller using artificial neural network does not need mathmatical model of the system including state observation, so it can be used for both linear and nonlinear system with no additional cost for nonlinearity. Designed multi layer neural network controller is composed of two parts, feedforward controller gives a steady state input & feedback controller gives transient input via minimizing the quadratic cost function. From the comparison of the results of the simulation of linear & nonlinear plant, the plant controlled by using neural network controller shows the trajectory similar to that of the plant controlled by an optimal controller.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.498-503
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• 1991

This paper presents a framework of a optimal supervisory controller, which consists of decision rules and the supervisory controller proposed by Ramadge and Wonham. From the presented framwork we obtain optimal control patterns minimizing the given cost functions. The properties of the presented optimal supervisory controller are discussed. Two examples are given to illustrate a designing method of the optimal supervisory controller.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1086-1089
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• 2012

We propose a near optimal controller design method for ramp metering based on SDRE (State Dependent Riccati Equation) approach. We parameterize the optimal nonlinear controller in terms of the solution matrices of an SDRE. We also give a simple algorithm to obtain the controller gain. Finally we give numerical results to show the effectiveness of the proposed near optimal traffic controller design method.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.4
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• pp.15-26
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• 1998

Full car model is needed for investigating as a entire dynamics of vehicle. In this study, 7DOF of full car model's dynamics is selected. This paper proposes the output feedback controller based on optimal control theory. Input data and output data from the optimal controller are used for neural network system identification of the suspension system. To do system identification, neural network which has robustness against nonlinearities and disturbances is adapted. This study uses back-propagation algorithm to train a multil-layer neural network. After obtaining a neural network model of a suspension system, a neuro-controller is designed. Neuro-controller controls suspension system with off-line learning method and multistep ahead prediction model based on the neural network model and a neuro-controller. The optimal controller and the neuro-controller are designed and then, both performances are compared through. For simulation, sinusoidal and rectangular virtual bumps are selected.

• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.4
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• pp.502-508
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• 2000

The amount of container freight is continuously increasing recently, but freight congestion problem frequently occurs at ports due to low efficiency of container crane in transportation and cargo handling. In this paper, a method for designing a fuzzy controller of the container crane system is presented. In this scheme a mathematical model for the system is obtained in state space representation. The response of the proposed fuzzy controller is compared with that of the optimal controller at the same condition. Through the simulation results, the performance of the fuzzy controller was observed better than that of optimal controller in respect of reference change, disturbances and parameter change. The fuzzy controller was also more stable and robust than the optimal controller.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.471-478
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• 2007

In this paper, an optimal Wiener-Hopf decoupling controller formula is obtained which is expressed in terms of rational matrices, thereby readily allowing the use of state-space algorithms. To this end, the characterization formula for the class of all realizable decoupling controller is formulated in terms of rational functions. The class of all stabilizing and decoupling controllers is parametrized via the free diagonal matrices and the optimal decoupling controller is determined from these free matrices.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.2
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• pp.85-93
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• 2013

The proportional plus integral(PI) feedback control manner has been used in many general industrial fields such as refrigeration system because of its simple design process and favorable control performance. This paper deals with optimized PI controller design of the refrigeration system based on evaluation functions such as integrated absolute error(IAE). The suggested optimal PI gains can be easily calculated by a simple program and the optimal controllability satisfying the evaluation function can be assured. Furthermore, at the initial step of controller design, the suggested optimal gain is able to reflect some noise disturbances caused by an inverter which drives variable speed compressors. The validity of the suggested optimal gain is investigated by some simulations and experiments to verify its efficiency. From the results of comparing control performance between the optimal PI controller based on the evaluation function and the PI controller designed by the Matlab tuner which was known as the most popular gain tuner, the optimal PI controller showed more desirable control performance especially in transient responses.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.149-152
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• 2002

The aim of this study is to analyse the problems occurred by using classical algorithm to synthesize the H$\infty$ optimal controller. The obtained result of analysis applied to the composition of algorithm for the new H$\infty$ optimal controller which was introduced in this study. The study investigates and compares H$\infty$ optimal controller formed by new algorithm with the one formed by classical algorithm. In particular, robustness related to the robust control is systematically described by using the composition of algorithm for the classical H$\infty$ optimal controller. In addition, the flow charts classified into classical algorithm and new one are discussed to synthesize the H$\infty$ optimal controller.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.172.2-172
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• 2001

We introduce a new stable feedback controller eventually converges to a conventional SDRE(State Dependent Riccati Equation) based optimal (suboptimal) controller. On conventional SDRE, the optimal control input should be obtained by backward integration of the SDRE at each control point. The proposed controller is given by direct forward integration of a proposed SDRE. This fact enables fast computation and easy implementation. On concerning a state dependent system, the proposed controller may be a candidate to the conventional SDRE based optimal controller if the system is slow varying with states. Though the controller is fast and easy to implement it is not able to cope with a fast varying system. We introduce an optimality index, which indicates how far the proposed controller is deviated from the solution of the convectional SDRE. If the index escapes a ...