• 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.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.17-20
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• 2001

In this paper, we design a nonlinear adaptive controller using wavelet neural network. The method proposed in this paper performs for a nonlinear system with unknown parameters, identification with using a wavelet neural network, and then a nonlinear adaptive controller is designed with those identified informations. The advantage of the proposed control method is simple to design a controller for unknown nonlinear systems, because we use the identified informations and design parameters are positioned within a negative real part of s-plane. The simulation results showed the effectiveness of proposed controller design method.

• Journal of Power System Engineering
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• v.21 no.4
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• pp.42-50
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• 2017

A velocity controller using a modified model reference adaptive controller (M-MRAC) and a projection operator for a fish sorting belt conveyor system with uncertainty parameters, input saturation and bounded disturbances is proposed in this paper. To improve the tracking performance and robustness of the proposed controller in the presence of bounded disturbances, the followings are done. Firstly, the reference model for the conventional model reference adaptive controller (CMRAC) is replaced by a modified reference model for a M-MRAC to reduce unexpected high frequency oscillation in control input signal when the adaptation rate is increased. Secondly, estimated parameters in an adaptive law are varied smoothly under bounded external disturbances and a projection operator is utilized in an adaptive law for the proposed M-MRAC controller to be robust. Thirdly, an auxiliary error vector is introduced for compensating the error dynamics of the system when the saturation input occurs. Finally, the experimental results are shown to verify the better effectiveness and performance of the proposed controller under the bounded disturbance and saturated input than that of a CMRAC.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.164-167
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• 2004

In the paper is proposed a hierarchical adaptive fuzzy controller 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 hierarchical adaptive fuzzy controller consists of a robust indirect adaptive fuzzy controller for balancing, a forced disturbance generator which emulates heuristic control strategy, and a supervisory decision maker for the arbitration of two control objectives It is proved that all the signals in the overall system are bounded. Simulation results are given to verify the proposed adapt i ye fuzzy control method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.10
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• pp.486-493
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• 2000

This paper presents an application to a multimachine power system of power system stabilizer using revised pole shift adaptive algorithm. Controller parameters are determined by using adaptive control theory in order to maintain optimal operation of generator under the various operating conditions. To determine the optimal parameters of controller and overcome the problem of pole placement algorithm, this paper presents pole shift algorithm revised pole shift factor. Also, the difference between the speed deviation with weighted factor and voltage deviation is used as the input signal of adaptive controller, which provides good damping characteristics. The results tested on a multimachine power system verify that the proposed controller has better dynamic and transient performance than conventional controller.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.21 no.3
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• pp.1-8
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• 2013

An application of adaptive flight controller is required for the non-linear and high uncertain system that configuration of tiltrotor aircraft is dramatically changed from rotary wing mode to fixed wing mode. In this paper, the applicable adaptive controller for the tiltrotor aircraft was designed using Neural Networks and DMI (Dynamic Model Inversion). The performance of the SCAS (Stability and Control Augmentation System) was simulated against manned military specification, using the fullscale model of 'Smart UAV(Unmanned Aerial Vehicle)' developed by Korea Aerospace Research Institute. And Neural Networks based adaptive controller was verified through its whole operating envelope using the established HQ (Handling Quality) criteria.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.4
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• pp.112-120
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• 2001

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing the approach of an adaptive dual fuzzy logic. Some goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a high building, when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of a fuzzy rule base. Controls for co-operation among elevators in a group control algorithm arte essential, and the most critical control function in the group controller is an effective and proper hall call assignment of elevators. The group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.578-581
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• 2001

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing approach of an adaptive dual fuzzy logic. A goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a building. when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of fuzzy rule base. Control for co-operation among elevators in group control algorithm are essential, and the most critical control function in group controller is a effective and proper hall call assignment of elevators. Thy group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.157-160
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• 2000

In this paper, the development of a new group controller for high-speed elevator is carried out utilizing approach of an adaptive dual fuzzy logic. A goals of control are the minimization of waiting time, mean-waiting time and long-waiting time in a high building, when a new hall call is generated, adaptive dual fuzzy controller evaluate traffic pattern and change appropriately the membership function of fuzzy rule, base. Control for co-operation among elevators in group control algorithm are essential , and the most critical control function in group controller is a effective and proper hall call assignment of elevators. The group elevator system utilizing adaptive dual fuzzy control reveals a great deal of improvement on its performance.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1507-1508
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• 2008

In this paper, we propose a direct robust adaptive backstepping speed controller for induction motors system. A robust adaptive backstepping controller is designed using high order neural networks(HONN), which avoids the singularity problem in adaptive nonlinear control. The stability of the resulting adaptive system with proposed adaptive controller is guaranteed by suitable choosing the design parameter and initial conditions. HONN are used to approximate most of uncertainties which are derived from unknown motor parameters, load torque disturbances and unknown nonlinearities. The applicability of the proposed scheme is tested simulation.