• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.205-216
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• 2020

This study seeks to empirically analyze the effects of core self-evaluation and adaptive selling behavior on sales performance for female salespersons engaged in door-to-door sales through the face-to-face channel in the wellness industry. This study seeks to examine the importance of adaptive selling, through, salespeople derive appropriate strategies in response to market changes. For female salespeople who use face-to-face channels, this study empirically investigated the relationship between core self-evaluation and adaptive selling, and effects on sales performance. A 31-item survey was constructed, based on prior research. We selected six door-to-door sales companies in South Korea and conducted one-to-one interviews with female salespeople in the Seoul metropolitan area and analyzed 208 pieces of significant data. Results demonstrated that among the core self-evaluation factors for female salespeople, self-esteem, self-efficacy, and neuroticism had an effect on adaptive selling factors, while locus of control did not. These factors were found to affect sales performance through the mediating role of adaptive selling. Improvements in the adaptive selling capabilities of female salespeople in charge of face-to-face channels positively affected sales performance. Management efforts are required to enhance self-esteem, self-efficacy, or neuroticism. These results suggest that companies should support enhancing individual adaptive selling capabilities of their salespeople.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1220-1230
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• 2006

In this paper, we propose a flew technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.94-104
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manpulators to achieve accurate trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed contorl scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Morever, this scheme does not require an accurate dynamic modeling nor values of manpipulator parameters and payload. Performance of the adaptive controller is illustated by simulation and experimental results for a SCARA robot.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1087-1094
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• 2014

In general, a speaker generates nonlinear distortions owing to a design principle, manufacturing process, and so on, which decreases and changes a sound quality. So, if the speaker is linearized by compensating these nonlinear distortions, the sound quality and satisfaction can be increased. In this paper, a new adaptive controller was proposed to be applied for compensating nonlinear distortions of a speaker. Through computer simulations as well as the analytical analysis, it could be shown that it is possible for both conventional adaptive controller and proposed adaptive controller, to be applied for linearizing the speaker with nonlinear distortions. Also, the simulations results demonstrated that the proposed adaptive controller may have faster convergence speed and better capability of compensating the nonlinear distortion than the conventional adaptive controller with nearly equal computation complexity.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.6
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• pp.29-37
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• 1994

Active noise control of random noise which propatate in the vehicle cabin as a form of spherical wave is the target of this study. In the previous study, the adaptive algorithm for adaptive controller is presented for the application in active noise control system. And for the preliminary study of adaptive active noise control in vehicle cabin as a real system, a computer simulation is performed on the effectiveness of the adaptive algorithm in the amplitude of the pressure fluctuation. This work studies the implementation of multi-channel feedforward adaptive algorithm for the reduction of the noise inside a vehicle cabin using a number of secondary sources derived by adaptive filtering of reference noise source. Multi-channel adaptive feedforward algorithm are verified in numerical simulation and semi-experimental justification of developed system is made on a domestic passenger car. In the results of semi-experimental study, the noise of specific region in the interior of automobile are reduced for the appreciabe sound pressure level in the operating engine rpm and finally this study suggests the capabilities of the real time active noise control in 3 dimensional acoustic fields.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.573-578
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• 2002

In this paper, it Is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-negro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.1
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• pp.124-132
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• 2004

A hydraulic system is difficult to keep the performance due to non-linearity, load pressure which changes according to working condition and system parameter variation, the requirement of control algorithm has been risen in order to satisfy them. An adaptive control is a control method which is suggested to achieve a control object though plant characteristics change. In spite of the case that plant characteristics and the degree of variation are difficult to grasp, adaptive control can keep the characteristics of closed-loop system regularly. In this study GMVAC(generalized minimum variance adaptive control) combined with output error feedback is proposed in order to solve problems of non-minimum phase, vibration and overshoot in initial response of the plant. The control performance according to the variation of characteristics of the plant is evaluated by changing the supply pressure only.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.122-127
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• 2001

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.156-159
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• 1996

An adaptive predictive control for steam-reforming plant which consist of a steam-gas reformer and a waste heat steam-boiler was studied by using MIMO bilinear model. The simulation experiments of the process identification were performed by using linear and bilinear models. From the simulation results it was found that the bilinear model represented the dynamic behavior of a steam-reforming plant very well. ARMA model was used in the process identification and the adaptive predictive control. To verify the performance and effectiveness of the adaptive predictive controller proposed in this study the simulation results of steam-reforming plant control based on bilinear model were compared to those of linear model. The simulation results showed that the adaptive predictive controller based on bilinear model provides better performance than those of linear model.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.155-160
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• 2006

In the paper a robust indirect adaptive fuzzy controller is proposed for balancing and position control of the inverted pendulum system. Because balancing control rules of the pendulum and position control rules of the cart can be opposite, it is difficult to design an adaptive fuzzy controller that satisfy both objectives. To stabilize the pendulum at a specified position, the proposed fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing and a supervisory fuzzy controller which emulates heuristic control strategy and arbitrate two control objectives. It is proved that the signals in the overall system are bounded. Simulation results are given to verify the proposed adaptive fuzzy control method.