• Journal of Ocean Engineering and Technology
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• v.30 no.2
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• pp.134-140
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• 2016

An envelope protection system is a control system that allows a submarine to operate freely using its own operational envelope without exceeding the structural limit, dynamic limit, and control input limit. In this paper, an envelope protection system for the pitch angle of a submarine is designed using a dynamic trim algorithm. A linear quadratic regulator and artificial neural network are used for the true dynamics approximation. A submarine maneuvering simulation program developed using experimental data is used to validate the designed envelope protection system. Simulation results show the effectiveness of the designed envelope protection system.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.109-125
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• 2004

This paper deals with an optimal process control problem in production of hull structural steel plate with high defective rate. The main quality characteristic(dependent variable) is the internal quality(defect) of plates and is dependent on process parameters(independent variables). The dependent variable(quality characteristics) has three categorical ordinal data and there are 35 independent variables(29 continuous variables and 6 categorical variables). In this paper, we determine the main factors and to develop the mathematical model between internal quality predicted probabilities and the main factors. Secondly, we find out the optimal process condition of main factors through analysis of variance(ANOVA) using simulation. We consider three models to obtain the main factors and the optimal process condition: linear, quadratic, error models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.2
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• pp.261-265
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• 2014

This paper studies the problem of the sampled-data control for Lur'e system with nonlinearities. The nonlinearities are expressed as convex combinations of sector and slope bounds. It is assumed that the sampling periods are arbitrarily varying but bounded. By constructing a new augmented Lyapunov-Krasovskii functional which have an augmented quadratic form with states as well as the nonlinear function, the stabilizing sampled-data controller gains are obtained by solving a set of linear matrix inequalities. The effectiveness of the developed method is demonstrated by numerical simulations.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.2
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• pp.121-127
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• 2006

An analysis procedure for the combined problem of control algorithm and aeroelastic system which is based on the computational fluid dynamics(CFD) technique has been developed. The aerodynamic forces in the transonic region are calculated from the transonic small disturbance(TSD) theory. An linear quadratic regulator(LQR) controller is designed to suppress the transonic flutter. The optimal control gain is estimated by solving the discrete-time Riccati equation. The system identification technique rebuilds the CFD-based aeroelstic system in order to form an adequate system matrix which involved in the discrete-time Riccati equation. Finally the controller, that is constructed on the basis of system identification technique, is used to suppress the flutter phenomenon of the airfoil with attached store. This approach, that is, the CFD-based aeroservoelasticity design, can be utilized for the development of effective flutter controller design in the transonic region.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.266-268
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• 2006

In this paper, we design a Linear Quadratic Gaussian(LQG) controller for active suspensions. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Using an optimization-algorithm, Evolution Strategy(ES), we find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.179-182
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• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.95-99
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• 1994

Robot engineering is developed mainly in the field of intelligibility such as a manipulation. Considering the popularization of robots in the future, however, a robot should be studied from a viewpoint of saving energy because a robot is a kind of machine with a energy conversion. This paper deals with minimizing an energy consumption of a manipulator which is driven in a point-to-point control method. When a manipulator carries a heavy payload toward gravitation or the links are de-accelerated for positioning, the motors at joints generate electric energy. Since this energy can be regenerated to the source by using a chopper, the energy consumption of a manipulator is only heat loss by an electric and a frictional resistance of the motors. The minimization of the sum of these losses is reduced Lo a two-points boundary-value problem of an non-linear differential equation. The solutions are obtained by the generalized Newton-Raphson method in this paper. The energy consumption due to the optimum angular velocity patterns of two joints of a two-links manipulator is compared with conventional velocity patterns such as quadratic and trapezoid.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.982-987
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• 2009

On the controller switching time, even though on-line/off-line controller outputs are the same, a problem which deteriorates the performance of bumpless transfer can happen in case that any discrepancy between the two controller inputs is transferred directly to the controller output. In this paper, we analyze the cause of that phenomenon in existing research results and propose a new method which improves that problem. In order to solve this problem, the off-line controller is augmented to an anti-windup structure and an improved bumpless transfer method is derived by using the changed input of the off-line controller instead of the plant input. We exemplify the performance of the proposed method by comparing with the performance of the existing method via numerical examples.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.289-292
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• 2001

This paper concerns with a receding horizon estimator (RHE) for discrete-time linear systems subject to constraints on the estimate. In solving the optimization for every horizons, the past all measurement data outside the horizon is discarded and thus the arrival cost is not considered. The RHE in the current work is a finite impulse response (FIR) structure which has some good inherent properties. The proposed RHE can be represented in the simple matrix form for the unconstrained case. Various numerical examples demonstrate how including constraints in the RHE can improve estimation performance. Especially, in the application to the unknown input estimation, it will be shown how the FIR structure in the RHE can improve the estimation speed.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.