• Journal of the Korean Home Economics Association
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• v.48 no.8
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• pp.13-26
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• 2010

This study tested the path model with regard to how certain variables (control attribution, demand-control-support of activity, and control strategy) affected the elderly workers' subjective well-being(swb). In the path model, the exogenous variables were internal and external control attribution. We used demand-control-support of activity, and primary and secondary control strategies as mediating variables. The endogenous variable was each elderly worker's swb. Study participants were 205 elders participating in an "education activity". We used descriptive statistical analysis, Pearson's correlation and hierarchical multiple regression to examine data collected from structured interviews with the participants. Path analysis revealed the followings: First, secondary control strategy was the strongest predictor of participants' swb but internal control attribution, demand of activity, and support of activity also positively affected participants' swb. Second, internal control attribution indirectly affected the participants' swb. Finally primary control strategy negatively affected on the participants' swb.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1683-1693
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• 1997

In this paper, a new nonlinear dynamic model is derived for a 2-dimensional overhead crane based on a new definition of 2-degree-of-freedom swing angle, and a new anti-swing control law is proposed for the crane. The dynamic model and control law take simultaneous travel and traverse motions of the crane into consideration. The model is first linearized for small motions of the crane load about the vertical stable equilibrium. Then the model becomes decoupled and symmetric with respect to the travel and traverse axes of the crane. From this result, a decoupled anti-swing control law is proposed based on the linearized model via the loop shaping and root locus methods. This decoupled method guarantees not only fast damping of load-swing but also zero steady state position error with optimal transient response for the 2-dimensional motion of the crane. Finally, the proposed control method is evaluated by controlling the simultaneous travel and traverse motions of a 2-dimensional prototype overhead crane. The effectiveness of the proposed control method is then proven by the experimental results.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.7
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• pp.537-543
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• 2000

mathematical models for a hydraulic brake actuator and a brake control law for vehicle collision warning/collision avoidance (CW/CA) systems will be presented in this paper. The control law have been designed for optimzied safety and comfort. A solenoid-valve-controlled hydraulic brake actuator system for the CW/CA systems has been investigated, A nonlinear computer model and a linear model of the hydraulic brake actuator system have been developed. Both models were found to represent the actual system with good accuracy. Uncertainties in the brake actuator model have been considered in the design of the control law for the roubustness of the controller. The effects of brake control on CW/CA vehicle response has been investigated via simulations. The simulations were performed using the hydraulic brake system model and a complete nonlinear vehicle model. The results indicate that the proposed brake control law can provide the CW/CA vehicles with an opimized compromise between safety and comfort.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.139-145
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• 2006

A multi-variable Golden-Section adaptive controller is proposed for the tracking control of robotic manipulators with unknown dynamics. With a small sample time, the unknown dynamics of the robotic manipulator are denoted equivalently by a characteristic model of a 2-order multivariable time-varying difference equation. The coefficients of the characteristic model change slowly with time and some of their valuable characteristic relationships emerge. Based on the characteristic model, an adaptive algorithm with a simple form for the control of robotic manipulators is presented, which combines the multi-variable Golden-Section adaptive control law with the weighted least squares estimation method. Moreover, a compensation neural network law is incorporated into the designed controller to reduce the influence of the coefficients estimation error on the control performance. The results of the simulations indicate that the developed control scheme is effective in robotic manipulator control.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• Journal of the Korea Computer Graphics Society
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• v.22 no.1
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• pp.1-8
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• 2016

We propose a novel framework for controlling various and complex models using primitive model. To control original model, first we correspond original model to simplified primitive model that contains original model. After doing deformable simulation with primitive model, we compute original model by inversion of result. Since existing method can only control one type formed models, our method - which can control all difference formed models by only one primitive model - has contribution. In conclusion, we show results that efficiently and intuitionally control the various deformable models by using one example primitive model.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.373-376
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• 1986

This paper proposes a robust model following control system which realizes good properties such as asymptotic stability, disturbance rejection and model following with reduced sensitivity for plant parameter variation. This algorithm can be easily applied to the multivariable control systems and the control structure is simple. As an example the aircraft control system of a convair C-131B is designed and its characteristics are examined by simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.1
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• pp.35-41
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• 2010

In developing modern aircraft, the reconfiguration control that can improve the safety and the survivability against the unexpected failure by partitioning control surfaces into several parts has been actively studied. This paper deals with the reconfiguration control using model predictive control method considering the saturation of control surfaces under the control surface failure. Linearized aircraft model at trim condition is used as the internal model of model predictive control. We propose the controller that performs optimization using LMI (linear matrix inequalities) based semi-definite programming in case that control surface saturation occurs, otherwise, uses analytic solution of the model predictive control. The performance of the proposed control method is evaluated by nonlinear simulation under the flight scenario of control surface failure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2708-2715
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• 2012

This paper proposes a new sensorless speed control scheme of induction motor using Model Reference Adaptive Control and Direct Torque Control System. The Model Reference Adaptive Control System is based on the comparison between the outputs of Reference Model and Adjustable Model. The error between the estimated quantities obtained by the two models is used to drive a suitable adaptation mechanism which generates the estimated rotor speed for the Adjustable Model. And the Direct Torque Control scheme controls torque and flux by restricting the flux and torque errors within respective hysteresis bands, and motor torque and flux are controlled by the stator voltage space vector using optimum inverter switching table. The simulation results of proposed method indicate good speed responses from the low speed range to the high, and also show favorable characteristics of load operation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.73-79
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• 2009

For the shake of control for movement object, control theory like neural network, nonlinear model predictive control(NMPC) is realized on digital high speed computer. Predictor of flight control system(FCS) based nonlinear model predictive control has to be satisfied with response for hard real-time to perform applications on each module in the FCS. Simultaneously, It gives a serious consideration accuracy to give full play to FCS's performance. Error of mathematical aspect affects realization of whole algorithm. But factors of bring mathematical error is not considered to calculate final accuracy on parameter of predictor. In this paper, Predictor was made using load control model on the digital computer for design FCS at hard real-time and is shown response time on realization algorithm. And is shown realization algorithm of high effective predictor over the accuracy. The predictor was realized on the load control model using Euler method, Heun method, Runge-Kutta and Taylor method.