• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.523-530
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• 2007

Crane systems are very important in industrial fields to carry heavy objects such that many investigations about control of the systems are actively conducted for enhancing its control performance. This paper presents an adaptive control approach using the model matching for a complex 3-DOF nonlinear crane system. First, the system model is linearized through feedback linearization method and then PD control is applied in the approximated model. This linear model is considered as nominal to derive corrective control law for a perturbed crane model using Lyapunov theory. This corrective control is primitively aimed to compensate real-time control deviation due to partially known perturbation. We additionally study stability analysis of the crane control system using Lyapunov perturbation theory. Evaluation of our control approach is numerically carried out through computer simulation and its superiority is demonstrated comparing with the classical control.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1634-1635
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• 2007

본 논문은 갠트리 크레인의 시뮬레이터를 제작하여 적응형 흔들림 제어기를 설계한다. 흔들림 감지는 디지털 카메라 센서를 이용하였으며 모델기반 적응제어를 이용하여 제어규칙을 산출한다. 제어규칙은 리아푸노브 안정성이론을 적용하였으며 정의된 리아푸노브 함수의 미분식이 음수를 갖기 위한 크레인의 적응형 제어입력을 계산한다. 제안한 제어기의 성능을 검토하기 위하여 실시간 제어실험을 실시하였으며 이송체의 무게 변화에 대한 적응성을 검토한다. 또한 기존의 PI 제어기도 함께 실험하여 성능의 비교 검토한다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.1
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• pp.95-100
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• 2013

This paper presents a new state feedback control approach for communication networks based control systems in which control input and output observation time-delay natures are generally occurred in practice. We first establish a generic state feedback control framework based on well-known linear system theory. A maximum time-delay value which allows critical stability of whole control system are defined to make a positive definite Lyapunov function which is mathematically composed of controlled system states. We analytically derive its control parameters by using a steepest descent optimization method in order to guarantee a stability condition through Lyapunov theory. Computer simulation is numerically carried out for demonstrating reliability of the proposed NCS algorithm and a comparative study is accomplished to prove its superiority for which the traditional control approach for NCS is made use of under same simulation scenarios.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.89-97
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• 2008

Chaotic behavior in motor systems is undesired dynamics in real-time implementation since the speed is oscillated in a wide range and the torque is changed by a random manner. We present an adaptive control approach for time-varying permanent-magnet synchronous motors (PMSM) with chaotic phenomenon. We consider that its parameters are changed randomly within certain bounds. First, a nonlinear system model of a PMSM is transformed to derive a nominal linear control strategy. Then, an auxiliary control for compensating real-time control error occurred by system perturbation due to parameter change is designed by using Lyapunov stability theory. Numerical simulation is accomplished for evaluating its efficiency and reliability comparing with the traditional control method. Additionally, we test our control method in real-time motor experiment including a PSoC based drive system to demonstrate its practical applicability.