• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1437-1445
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• 2014

In this paper a novel method for angular position determination using sensors with sin/cos output and without an excitation signal, is presented. The linearization of the sensor transfer characteristic and digitalization of the measurement results are performed simultaneously with a goal to increase the measurement resolution. This improvement is particularly important for low angular velocities, and can be used to increase the resolution of incremental Hall, magnetic and optical sensors. This method includes two phases of sin/cos signal linearization. In the first linearization phase the pseudo-linear signal is generated. The second linearization phase, executed by the two-stage piecewise linear ADC, is an additional linearization of the pseudo-linear signal. Based on the LabVIEW software simulations of the proposed method, the contribution of each processing phase to a final measurement error is examined. After the proposed method is applied within $2{\pi}$ [rad] range, the maximal nonlinearity is reduced from 0.3307 [rad] ($18.9447^{\circ}$) to $3{\cdot}10^{-4}$ [rad] ($0.0172^{\circ}$).

• Journal of the Chungcheong Mathematical Society
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• v.25 no.3
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• pp.381-391
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• 2012

In this paper, the formal linearization method is used to construct multisoliton solutions for three model of shallow water waves equations. The three models are completely integrable. The formal linearization method is an efficient method for obtaining exact multisoliton solutions of nonlinear partial differential equations. The method can be applied to nonintegrable equations as well as to integrable ones.

• Structural Engineering and Mechanics
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• v.30 no.1
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• pp.67-76
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• 2008

Limit cycle oscillations of a two-dimensional airfoil with quadratic and cubic pitching nonlinearities are investigated. The equivalent stiffness of the pitching stiffness is obtained by combining the linearization and harmonic balance method. With the equivalent stiffness, the equivalent linearization method for nonlinear flutter analysis is generalized to address aeroelastic system with quadratic nonlinearity. Numerical example shows that good approximation of the limit cycle can be obtained by the generalized method. Furthermore, the proposed method is capable of revealing the unsymmetry of the limit cycle; however the ordinary equivalent linearization method fails to do so.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.936-938
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• 1999

In this Paper, the design of a feedback linearization controller using multilayer neural network is proposed. The Proposed feedback linearization control scheme is designed by finding Lie derivatives from an identified neural networks. Lie derivatives are expressed as a combination of weights and neuron outputs. The proposed method is applied to an antenna arm problem and the simulation results show performance comparisons between the ordinary feedback linearization and the Proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.95.4-95
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• 2002

1. Introduction 2. Distance measurement using array 3. Linearization of CdS array characteristics 3.1. Crisp linearization of CdS array characteristics 3.2. Fuzzy logic linearization of CdS array characteristics 4. Magnetic Levitation System 4.1. Design of MLS 4.2. Implementation of MLS 4.3. Results of MLS 5. Conclusion

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.56.5-56
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• 2002

This paper studies on the feedback linearization of the looper system for hot strip mills, where the looper system plays an important role in regulating the strip tension. Firstly, nonlinear dynamic equations of the looper system are simply introduced. Secondly, using the static feedback linearization algorithm, a linear model of the looper system is obtained, of which usefulness is validated from comparison between the linear model and the nonlinear model, and design of LQI(Linear Ouadratic Integral optimal control) and ILQ (Inverse Linear Quadratic optimal control) looper control systems. In result, it is shown that the linear looper model by the feedback linearization well describes nonlin...

• International Journal of Internet, Broadcasting and Communication
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• v.6 no.2
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• pp.1-9
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• 2014

This paper presents a study on nonlinear time varying systems based on differential geometry. A brief introduction about controllability and involutivity will be presented. As an example, the exact feedback linearization and the approximate feedback linearization are used in order to show some application examples.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.198-198
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• 2000

In this paper, the linearization method of nonlinear systems via fuzzy controllers which can be the basic research for designing a systematic fuzzy controllers with singleton consequents is proposed. We regard a closed loop system as a canonical form and propose a methodology for linearization of nonlinear system which adjust the input at vertex using zero condition and affinity condition. Through some examples, we show the validity of the proposed method and it can be extended to the design problem of fuzzy controller.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.202-202
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• 2000

In this paper, the synchronous generator model which is derived from the swing equation and the Park's equation is transformed to an adequate form for feedback linearization. And the single controller is designed in order to play the role of both PSS and AVR. The result of the simulations shows that the stability of the system is guaranteed in the wide range of operating points.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.47-56
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• 1994

The dynamic feedback is well-known to be much more powerful tool in control than the static one. This paper deals with the dynamic feedback linearization of the nonlinear systems which are not (static) feedback linearizable. The dynamic feedback linearization problem is however too difficult to solve at momemt. Thus we introduce a restricted class of the dynamic feedback (pure integrators followed by the static feedback) which is often used to study the problems using dynamic feedback and obtain the necessary and sufficient conditions of the linearization problem using this class of the dynamic feedback.