• Journal of Navigation and Port Research
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• v.28 no.6
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• pp.469-474
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• 2004

In this paper, we study the posture control of an underwater vehicle with nonholonomic constraint. Generally, systems with nonholnomic constraints cannot be stabilized to an equilibrium points by smooth state feedback control. For the nonholonomic underwater vehicle system, we applied coordinate transformation to get multi-chained system We proposed non smooth feedback controller using backstepping method for stabilizing the multi chained form system Applying inverse input transformation to the non smooth feedback controller, we can get posture controller of the underwater vehicle with nonholonomic constraint. The proposed control scheme is applied to the posture control qf an underwater vehicle and verified the effectiveness of control strategy by numerical simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.5
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• pp.545-557
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• 2021

Engine is the main source of vibration that generates unwanted noise and vibration of vehicle chassis. Especially, in submarine applications, radiation of noise signatures can be detected at some distance away from the submarine using a sonar array. Thus quiet operation is crucial for submarine's survivability. This study addresses reduction of the force transmissibility originating from engines and transmitted to hull through engine mounts. An inertial damper, as an actuator of hybrid mount system, is addressed to reduce even further the level of vibration. Narrow band FxLMS algorithms are broadly used to cancel the vibration of engine mount because of its excellent performance of canceling narrow band noise. However, in real active dampers, the maximum displacement of damper mass is kinematically restricted. When the control input signal from the FxLMS algorithm exceeds this limitation, the damper mass will collide with the mechanical stops and results in many problems. Originated from these, a modified narrow band FxLMS algorithm based on the equalizer technique with the maximum allowable displacement of active damper mass is proposed in this study. Some simulation results showed that the propose algorithm is effective to suppress vibration of engine mount while ensuring given displacement constraint.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.12
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• pp.991-997
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• 2002

The concept of feasible & invariant region plays an important role to derive closed loop stability and achie adequate performance of constrained receding horizon predictive control. In this paper, we define a complex polyhedral feasible & invariant set for all stabilizable input-constrained linear systems by using a complex transform and propose a one-norm based receding horizon control scheme using these invariant sets. In order to get a larger stabilizable set, a convex hull of invariant sets which are defined for different state feedback gains is used as a target invariant set of the constrained receding horizon control. The proposed constrained receding horizon control scheme is formulated so that it can be solved via linear programming.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.6 s.183
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• pp.88-95
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• 2006

In this paper, the gain-scheduled control design proposed in the previous paper has been applied to a target tracking system. In such system, it is needed to attenuate disturbance effectively as long as control input satisfies the given constraint on its magnitude. The scheduled gains are derived in the framework of linear matrix inequality(LMI) optimization by means of the MatLab toolbox. Its effectiveness is verified along with the simulation results compared with the conventional optimum constant gain and the scheduled gain control with constant Q matrix cases.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.12
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• pp.65-73
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• 2007

In this paper, the gain scheduled state feedback and disturbance feedforward control design proposed in the previous paper has been applied to a simple matching system and a turret stabilization system. In such systems, it is needed to attenuate disturbance response effectively as long as control input satisfies the given constraint on its magnitude. The scheduled control gains are derived in the framework of linear matrix inequality(LMI) optimization by means of the MatLab toolbox. Its effectiveness is verified along with the simulation results compared with the conventional optimum constant gain control and the scheduled state feedback control cases.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.327-330
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• 1996

It is well known that the controller output limits have a signifiant effect on the closed loop system performance. Considering the input constraints in GPCF, an effective selection method of the control weighting(.gamma.) is proposed to reduce the amplitude and the rate of control signals so that control signals lie within the limits. It is based on the relation between control weighting(.gamma.) and optimal solution of the unconstrained GPCF. The GPCFIC algorithm chooses an .gamma. at each sampling time so that all unconstrained GPCF output over the control horizon satisfy the rate and the amplitude constraints. In order to evaluate the performance of the GPCFIC, the computer simulations have been done for level control of PWR steam generator in low power operation and shown satisfactory results.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.6
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• pp.90-98
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• 1997

A time-optimal control law for quick, strongly nonlinear systems has been developed and demonstrated. This procedure involves the utilzation of neural networks as state feedback controllers that learn the time-optimal control actions by means of an iterative minimization of both the final time and the final state error for the systems with constrained inputs and/or states. A neural identifier or a genetic algorithm identifier could be utilized for modeling the partially known systems and the unknown systems. The nature of neural networks as a parallel processor would circumvent the problem of "curwe of dimensionality". The control law has been demonstrated for both a torque input motor and a velocity input motor identified by a genetic algorithm called GENOCOPed GENOCOP.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.32-38
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• 2013

This paper presents collision avoidance using model predictive control algorithm. A model predictive control algorithm determines lateral tire force and yaw moment and steering angle input and differential braking input is determined from lateral tire force and yaw moment. A constraint for model predictive control is designed for obstacle avoidance. A objective function is designed to minimize lateral tire force and yaw moment input and to follow changed lane after collision avoidance. The performance of proposed algorithm has been investigated via computer simulation conducted to vehicle dynamic software CARSIM and Matlab/Simulink.

• Structural Engineering and Mechanics
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• v.25 no.1
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• pp.21-37
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• 2007

In this study a stochastic approach for linear viscous dampers design adopted for seismic protection of buildings is developed. Devices optimal placement into the main structure and their mechanical parameters are attained by means of a reliability-based optimum design criterion, in which an objective function (O.F.) is minimized, subject to a stochastic constraint. The seismic input is modelled by a non stationary modulated Kanai Tajimi filtered stochastic process. Building is represented by means of a plane shear type frame model. The selected criterion for the optimization searches the minimum of the O.F., here assumed to be the cost of the seismic protection, i.e., assumed proportional to the sum of added dampings of each device. The stochastic constraint limits a suitable approximated measure of the structure failure probability, here associated to the maximum interstorey drift crossing over a given threshold limit, related, according with modern Technical Codes, to the required damage control.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.98-102
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• 2002

In this paper i offer a new part-of-speech tagging method for Korean, it can solve difficulty of statistical data acquisition and ambiguities due to same part-of-speech stream input and make good use of the Corpus. This method can solve that the corpus don't have huge. This method uses pattern information about part-of-speech among eojols and constraint-rules in order to perform part-of-speech tagging. The Constraint-rule is used to select appropriate part-of-speech pattern.