• Journal of Ocean Engineering and Technology
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• v.2 no.2
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• pp.37-45
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• 1988

A dynamically positioned vessel must be capable of maintaining a specified position and direction by controlling the thruster devices. The motions of a vessel are often assuned to tne sum of low frequency(LF)motions and high frequency(HF)motions. The former is mainly due to wind, current and second order wave forces, while the latter is mainly due to first order wave forces. In order to avoid the high frequency thruser modulation, the control system must include filters to estimate the low frequency motions from the measured motion signals, This paper presents a control system based on Kalman filtering technique and optimal control tyeory. Using the combined kalmam filter, LF motion estimates and HF ones are achieved from the motion measurement of the vessel. The estimated low frequency motions are used as inputs to the dynamic positioning system. The thruster modulation is minimized using the optimal control theory; Linear Quadratic Gaussian(LQG)controller. The performances of the Kalman filter and the dynamic positioned vessel are investigated by computer simulation.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.708-710
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• 2004

This paper studies a multirate sampled-data control for LTI systems by using the digital redesign (DR) method. In this note, to well tackle the problem associated with both the state matching and the stabilization, our nobel strategy is to minimize the linear quadratic cost function. The main features of the proposed method are that i) the delta-operator-based descretization method is applied to improve the state-matching performance in the fast sampling limit and/or the large input multiplicity; ii) the proposed multirate control scheme can improve the state-matching performance in the long sampling limit; iii) some sufficient conditions that guarantee the stability of the closed-loop discrete-time system and provide a guarantee cost for the cost function can be formulated in the LMIs format; and iv) an optimal sampled-data controller in the sense of minimizing the upper bound of the cost function is also given by means of an LMI optimization procedure.

• Smart Structures and Systems
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• v.20 no.3
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• pp.273-283
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• 2017

This paper presents and compares three feedback control strategies for active control of noise inside a 3-D vibro-acoustic cavity. These are a) control strategy based on direct output feedback (DOFB) b) control strategy based on linear quadratic regulator (LQR) to reduce structural vibrations and c) LQR control strategy with a weighting scheme based on structural-acoustic coupling coefficients. The first two strategies are indirect control strategies in which noise reduction is achieved through active vibration control (AVC), termed as AVC-DOFB and AVC-LQR respectively. The third direct strategy is based on active structural-acoustic control (ASAC). This strategy is an LQR based optimal control strategy in which the coupling between the various structural and the acoustic modes is used to design the controller. The strategy is termed as ASAC-LQR. A numerical model of a 3-D rectangular box cavity with a flexible plate (glued with piezoelectric patches) and with other five surfaces treated rigid is developed using finite element (FE) method. A single pair of collocated piezoelectric patches is used for sensing the vibrations and applying control forces on the structure. A comparison of frequency response function (FRF) of structural nodal acceleration, acoustic nodal pressure, and piezoelectric actuation voltage is carried out. It is found that the AVC-DOFB control strategy gives equal importance to all the modes. The AVC-LQR control strategy tries to consume the control effort to damp all the structural modes. It is seen that the ASAC-LQR control strategy utilizes the control effort more intelligently by adding higher damping to those structural modes that matter more for reducing the interior noise.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.747-752
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• 1999

In the fast sampling limit, the delta operator model tends to the analog system model. This fundamental property of the delta operator model unifies continuous and discrete time control system. In this paper, we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that convers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control. The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2602-2604
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• 2000

In this paper, we study robust linear optimal model following servo system in the presence of disturbances and parameter perturbations. A technique to directly design the generalized differential operator based unified control system that covers both differential operator based continuous time and delta operator based discrete time case is presented. The quadratic criterion function for a linear system is used to design the robust unified servo control system. This servo control system is designed by applying a simple genetic algorithm to follow the output of the reference model optimally. The characteristics of the proposed servo system are analysed and simulated to verify the robustness.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.91-94
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• 1985

A method optimizing selection of a state weighting matrix is presented. The state weight-ing matrix is chosen so that the closed-loop system responses closely match to the ideal model responses. An algorithm is presented which determines a positive semidefinite state weighting matrix in the linear quadratic optimal control design problem and an numerical example is given to show the effect of the present algorithm.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.557-572
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• 2004

Control systems are used to limit structural lateral deflections during large external loads such as winds and earthquakes. Most recently, the semi-active control approach has grown in popularity due to inexpensive control devices that consume little power. As a result, recently designed control systems have employed many semi-active control devices for the control of a structure. In the future, it is envisioned that structural control systems will be large-scale systems defined by high actuation and sensor densities. Decentralized control approaches have been used to control large-scale systems that are too complex for a traditional centralized approach, such as linear quadratic regulation (LQR). This paper describes the derivation of energy market-based control (EMBC), a decentralized approach that models the structural control system as a competitive marketplace. The interaction of free-market buyers and sellers result in an optimal allocation of limited control system resources such as control energy. The Kajima-Shizuoka Building and a 20-story benchmark structure are selected as illustrative examples to be used for comparison of the EMBC and centralized LQR approaches.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.35 no.5
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• pp.412-418
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• 2007

An inverse optimal problem for homing guidance with angular constraint is addressed. The gains of BPN(Biased PN) are investigated by duality analysis related to the weighting matrices of the performance index in the LQ control problem. Moreover, the criteria for the existence of optimal gains are derived from the generalized Riccati equation. Based on the conditions we achieve the gain set of BPN to be optimal solution to the LQ problem with terminal constraints. To validate and demonstrate the proposed approach 3-DOF simulations are carried out.

• Journal of Navigation and Port Research
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• v.31 no.4
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• pp.289-293
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• 2007

In this paper, new application of adaptive neural network to design a ship's Rudder-Roll Damping(RRD) control system is presented Firstly, the ANNAI neural network controller is presented. Secondly, new RRD control system using this neural network approach is developed. It uses two neural network controllers for heading control and roll damping control separately. Finally, Computer simulation of this RRD control system is carried out to compare with a linear quadratic optimal RRD control system; discussions and conclusions are provided. The simulation results show the feasibility of using ANNAI controller for RRD. Also, the necessity of mathematical ship model in designing RRD control system is removed by using NN control technique.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.3
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• pp.37-53
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• 2016

This paper deals with an optimal output control for Space Shuttle Main Engine (SSME), a liquid propellant rocket engine using a staged-combustion cycle. For this purpose, we modeled simplified mathematical model of SSME using each SSME component divided into 7 major categories and found trim points called Rated Propulsion Level (RPL). For design the closed-loop system of SSME, we designed optimal output feedback Linear Quadratic Regulation (LQR) control system using SSME linearized model under RPL 104% and demonstrated the performance of the controller through numerical simulation.