• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.320-322
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• 1993

In this paper, the decentralized adaptive control scheme is applied to the control of drum type boiler system. Because the scheme requires the stability of interconnections, static feedback is used to satisfy the requirement of the scheme. From a priori knowledge of the system, system parameter estimates are bounded to prevent parameter drifting. Computer simulation shows that the decentralized adaptive control is suitable for the control of drum type boiler system and robust in the presence of disturbance.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.177-182
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• 2003

The robust output tracking control problem of general nonlinear MIMO systems is discussed. The robustness against parameter uncertainties is considered. In this paper, we proposed the robust output tracking control scheme for a class of MIMO nonlinear dynamical systems using output feedback linearization method. The presented control scheme is based on the VSS. We assume that the nonlinear dynamical system is minimum phase, the relative degree of the system is r$_{1}$＋r$_{2}$＋…r$_{m}$$\leq$ n and zero dynamics is stable. It is shown that the outputs of the closed-loop system asymptotically track given output trajectories despite the uncertainties while maintaining the boundedness of all signals inside the loop. And we verified that the proposed control scheme is then applied to the control of a two degree of freedom (DOF) robotic manipulator with payload.d.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.2
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• pp.145-149
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• 2015

This paper introduces a sway suppression control for container cranes with unknown payloads and sway rates. With no priori knowledge concerning the magnitude of payload mass and sway rate, the proposed control maintains superior sway suppressing and trolley positioning against external disturbances. The proposed scheme combines a second order sliding mode control and an adaptive control to cope with unknown payloads. A second order sliding mode control without feedback of the sway rate is first designed, which is based on a class of feedback linearization methods for stabilization of the under-actuated sway dynamics of the container. Under applicable restrictions of the magnitude of payload inertia and sway rate, a linear regression model is obtained, and an adaptive control with a payload estimator is then designed, which is based on Lyapunov stability methods for the fast attenuation of trolley oscillations in the vicinity of the target position. The asymptotic stability of the overall closed-loop system is assured irrespective of variations of rope length. Simulation are shown in the existence of initial sway and external wind disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.382-385
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• 2003

In this paper, in order to improve the control performance of piezoelectric actuator, an integrated control structure is proposed. The control structure consists of inverse hysteresis model , to compensate the hysteresis nonlinearty problem, and feedforward - feedback controller to give a good tracking performance. The inverse hysteresis model and neural network are used as feed-forward controller, and PID controller is used as a feedback controller. From diverse experiments it is concluded that the proposed control scheme gives good tracking performance than the classical control does.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.390-395
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• 2020

For some processes with saturations, economical operating points are on the saturation edges. Traditional feedback controllers cannot be used to regulate such processes on the saturation edges because there are abrupt dynamics changes and no feedback information at saturations. Optimization-based methods such as the model predictive control can treat this control problem without difficulty when the saturation levels and dynamics are known and not varying. Otherwise, an adaptation scheme to track the saturation levels and dynamics should be included. Here, for very simple methods to treat this control problem, two control methods based on the recent slope seeking method and the relay feedback method are proposed. Their performances are evaluated with simulations applying them to a second order liquid level system with saturation. Simulations show that these proposed control methods can find and maintain operating point of the saturation edge under 5% relative error.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.275-290
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• 2014

In this paper, Simple Adaptive Control (SAC) method is used to mitigate the detrimental effects of earthquakes on MR-damper equipped structures. Acceleration Feedback (AF) is utilized since measuring the acceleration response of structures is known to be reliable and inexpensive. The SAC is simple, fast and as an adaptive control scheme, is immune against the effects of plant and environmental uncertainties. In the present study, in order to translate the desired control force into an applicable MR damper command voltage, a neural network inverse model is trained, validated and used through the simulations. The effectiveness of the proposed AF-based SAC control system is compared with optimal H2/LQG controllers through numerical investigation of a three-story model building. The results indicate that the SAC controller is substantially effective and reliable in both undamaged and damaged structural states, specifically in reducing acceleration responses of seismically excited buildings.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1162-1167
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• 2004

This paper presents the design methodology of digital fuzzy controller(DFC) for the systems with time-delay. We propose the fuzzy feedback controller whose output is delayed with unit sampling period and predicted. The analysis and the design problem considering time-delay become easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy system with time-delay is solved by linear matrix inequality(LMI) theory. Convex optimization techniques are utilized to solve the stable feedback gains and a common Lyapunov function for designed fuzzy control system. To show the effectiveness the proposed control scheme, the network control example is presented.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.6
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• pp.932-938
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• 2009

As a stringing troy wire is installed by manual operation, it is necessary to scheme the automatic system for stringing troy wire. To accomplish a task of this kind, in this paper an approach to designing controllers for the hybrid Position/Tension control of a stringing troy wire is presented. Position control system is designed based on equation of dc motor and motion equation of robot, it is controlled by feedback with a detected speed dc motor. Tension control system is designed based on equation of ac servomotor for generating torque and dynamic equation of a troy wire, it is controled by feedback with a detected tension. The control parameters is determined by simulation in independence operation of each system. To suppress a mutual interference that the disturbance occur in operating of two task at same time. Dynamic hybrid control is proposed by feed forward compensator with a disturbance accelerator and a step torque at start. The operation of proposed system is simulated and experimented, results is verified the utilities.