• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.283-283
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• 2000

In this paper, we deals with a decentralized control scheme with input compensation form for gantry crane systems. By considering the gantry crane's characteristics, the system is decentralized into two subsystems such as the travelling and sway subsystem, and the hoisting subsystem. For decentralizing the system, a simple algorithm is proposed using observability canonical form. The decentralized subsystems include unknown input which coupled with other subsystems and actuator failures. These unknown input and actuator failures are estimated by using PI observation techniques and those estimated values are used to construct an input compensation form. Lastly, the proposed decentralized control scheme far the gantry crane systems is verified by crane simulation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.5
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• pp.751-754
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• 2015

This paper deals with a robust speed control problem of a vertical one-link manipulator in the presence of parameter uncertainties and unknown input disturbance. Uncertain load weight causes an additional sinusoidal disturbance in the rotation of the link. In order to improve the robustness against parameter uncertainties and external input disturbances, this paper employs an internal model-based disturbance observer approach. Comparative computer simulations are performed to test the performance of the proposed controller. The simulation results show the enhanced performance of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.5
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• pp.625-630
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• 1986

In this paper, an adaptive observer based upon the exponentially weighted least-square method is implemented in the design of a model reference adaptive controller for an unknown time-invariant discrete single-input single-output linear plant. The adaptive observer estimates the padrameter vectors and initial state vector. The control input is determined so that the output of the plant converges to the output of the stable model reference.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.281-287
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• 2001

In this paper, we deal with a decentralized control scheme with input compensation form for gantry crane systems. By considering the gantry cranes characteristics, the system is decentralized into two subsystems, the travelling and swaying subsystem and the hoisting subsystem. For decentralizing the system, a simple algorithm is proposed using the observability canonical form. The decentralized subsystems include unknown inputs that one coupled with other subsystems and actuator failures. These unknown input and actuator failures are estimated by using PI observation techniques. And those estimated values are used to construct an input compensation form. Finally, the proposed decentralized control scheme for the gantry crane systems is verified by crane simulation.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.545-558
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• 2006

In this paper, PD-like visual servoing is modified in two ways: a sliding-mode observer is applied to estimate the joint velocities, and a RBF neural network is used to compensate the unknown gravity and friction. Based on Lyapunov method and input--to-state stability theory, we prove that PD-like visual servoing with the sliding mode observer and the neuro compensator is robust stable when the gain of the PD controller is bigger than the upper bounds of the uncertainties. Several simulations are presented to support the theory results.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.192-196
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.927-933
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Proceedings of the IEEK Conference
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• summer
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• pp.348-353
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.898-901
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• 1988

Up to now, using adaptive control method, Identification deals with system whose entire state variables and prameters are accessible for measurement. In practical situations, all the state variables cannot be measured and it is impossible to directly apply since the parameters of the system are unknown. Therefore, in this paper, using only input-output data, such a model of the system is not available since the parameters of the system are unknown. this leads to the concept of an adptive observer in which both the parameters and the state variable of the system are identified simultaniously. Lyapunov's direct method and Kalman-Yakubovich (K-Y) lemma are employed to ensure the stability of this schemes. The feature is that the signal and adaptive gain which is generated from filter is imposed upon feedback vector and then state variables and the unknown parameters can be identified. To show the usefulness of the proposed schemes, computer simulation result of unknown second-order system shows the effectiveness of the proposed schems.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1423-1427
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• 1997

This paper deals with an algebraic approach to FDI observer design procedure. In general, FDI observer can be designed a sLuenbrger-type and equations for unknown input and actuator fault estimation include derivation of system outputs which is not available from the measurement directly. At this point, this paper presents STWS approach which can convert the derivation procedure to the recursive algebraic form by using its orthogonality and disjointess to alleviate such problems.