• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.822-827
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• 2014

This paper presents a robust observer-based output feedback control for stabilization of linear time invariant systems with polytopic uncertainties. To this end, this paper not only finds a robust observer gain but also suggests how to determine the model used in the observer, which is not obvious due to model uncertainties in the conventional observer design method. The robust observer gain and the observer model are selected in a way that the whole closed-loop is stable by solving LMIs and BMIs (Linear Matrix Inequalities and Bilinear Matrix Inequalities). A simulation example shows that the proposed robust observer-based output feedback control successfully leads to closed-loop stability.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.21-26
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• 2003

The well-conditioned observer in a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic issues such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic issues such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_2$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic issues and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.39-44
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• 2003

It was shown that the robustness of deterministic observers with respect to modeling errors, measurement bias and round-off errors can be represented by a single performance index the condition number of the observer eigenvector matrix. In this paper, a robust observer for multi-output systems is designed using the left eigenstructure assignment, where the observer gain can not be determined uniquely with respect to the desired observer poles. Utilizing the eigenstructuer assignment for the robustness of the observer, the desired eigenvector matrix is selected to achieve the observer eigenvector matrix with the small condition number. The performance of the designed robust observer is evaluated in a spindle-drive simulation example where the load speed to be estimated based on the measured signals.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.10
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• pp.907-914
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• 2004

In this paper, we present a reduced-order observer for a class of nonlinear systems based on the input output linearization. While the most results in the literature presented full-order nonlinear observer, we proposed a procedure for the design of reduced-order observer far nonlinear systems that are not necessarily observable. Assuming that there exists a global observer fer internal dynamics and that certain functions are globally Lipschitz, we can design a global reduced-order observer An illustrative example is included that demonstrate the design procedure of the proposed reduced-order observer.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.12
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• pp.663-670
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• 2003

This paper deals with speed control of DC servo motor using a Adaptive high gain obserber. In this parer, the gain of the observer is properly set up using the fuzzy control and adaptive high gain observer that have a superior transient characteristic and is easy to implement compared the existing method is designed. In order to verify the performance of the Adaptive high gain observer which is proposed in this paper, it is compared estimate performance of High-gain Observer and Adaptive High Gain Observer with the computer simulation. Effectiveness of the proposed high gain observer is proved from the experiment to compare the case with a speed sensor to the case with Adaptive high gain observer in the speed control of DC servo motor.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.3
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• pp.89-94
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• 2000

A novel observer design methodology for linear time-invariant systems named the dynamic observer is presented. Efficient and plausible design algorithms are also provided. The dynamic observer is an extension of the usual static observer. The concept of the dynamic observer enlarges the capacity of observer design so much that well-developed advanced linear controller design techniques can be utilized to design observers. Both the dynamic observers in the form of standard and Luenburger types are considered. The essential characteristics of the dynamic observer to be qualified as an effective observer design scheme are addressed.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.2
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• pp.80-86
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• 2001

We design a sliding mode cascade observer to estimate derivatives of the output. In the 1st step of the observer, the output will be estimated, and the 1st order derivative of the output will be estimated via the 2nd step of the observer. Also, nth order derivative of the output will be estimated in the n+1th step of the observer. Exponential convergence of the estimation errors is shown under the bounded initial condition. Numerical examples will be presented to show the validity of the proposed observer.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.53-56
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• 2002

This paper presents neural observer that used to deadbeat load torque observer. Most practical systems are nonlinear, and it is general practice to use linear models to simplify their analysis and design. However, the locally linearized model is invalid for a large signal change. The neural observer is suggested to increase the performance of the load torque observer and main controller The output error and estimeted state is trianed by neural network of neural observer. As a result, the state estimation error is minimised and deadbeat load torque observer make use of corrected esimation state. To reduce of the noise effect of deadbeat load torque observer, the post-filter which is implemented by MA process, is adopted. As a result, the proposed control system becomes a robust and precise system against the load torque. A stability and usefulness, through the verified computer simulation, are shown in this paper.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.484-487
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• 2003

In this paper describes a design of Adaptive high gain observer. The gain of the observer is properly set up using the fuzzy control and adaptive high gain observer that have a superior transient characteristic and is easy to implement compared the existing method is designed. In order to verify the performance of the Adaptive high gain observer which is proposed in this paper, it is compared estimate performance of High-gain Observer and Adaptive High Gain Observer with the computer simulation. Effectiveness of the proposed high gain observer is proved from the simulation to compare the case with a speed sensor to the case with Adaptive high gain observer in the speed control of DC servo motor.

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1150-1158
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• 2004

In this paper, we present an adaptive observer for nonlinear systems that include unknown constant parameters and are not necessarily observable. Sufficient conditions are given for a nonlinear system to be transformed by state-space change of coordinates into an adaptive observer canonical form. Once a nonlinear system is transformed into the proposed adaptive observer canonical form, an adaptive observer can be designed under the assumption that a certain system is strictly positive real. An illustrative example is included to show the effectiveness of the proposed method.