• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.939-942
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• 1989

Most of systems are included nonlinear characteristics in practice. One might be faced with difficulties when problems of nonlinear systems are solved. In this paper we present a formal linearization method of nonlinear systems by using the trigonometric Fourier expansion on the state space considering easy inversion. An error bound, an application, and a compensation of this method are also investigated.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.48.2-48
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• 2001

This paper deals with robust integral tracking control problem based on Lyapunov method via FL(Feedback Linearization) in order to solve a reference tracking problem of nonlinear system with parameter uncertainties. To overcome a restrictive matching condition the uncertainties is characterized in a suitable form. The design procedure which combine FL and LMIs(Linear Matrix Inequalities) based on Lyapunov method to achieve the robust performance and stability is developed. Finally, the performance of proposed controller is demonstrated via simulation of a linear reference tracking problem in the MLS(Magnetic levitating System).

• Journal of the Optical Society of Korea
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• v.15 no.4
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• pp.386-393
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• 2011

In this study, we report an effective k-domain linearization method with a pre-calibrated indexed look-up table. The method minimizes k-domain nonlinear characteristics of a swept source optical coherence tomography (SS-OCT) system by using two arrays, a sample position shift index and an intensity compensation array. Two arrays are generated from an interference pattern acquired by connecting a Fabry-Perot interferometer (FPI) and an optical spectrum analyzer (OSA) to the system. At real time imaging, the sample position is modified by location movement and intensity compensation with two arrays for linearity of wavenumber. As a result of evaluating point spread functions (PSFs), the signal to noise ratio (SNR) is increased by 9.7 dB. When applied to infrared (IR) sensing card imaging, the SNR is increased by 1.29 dB and the contrast noise ratio (CNR) value is increased by 1.44. The time required for the linearization and intensity compensation is 30 ms for a multi thread method using a central processing unit (CPU) compared to 0.8 ms for compute unified device architecture (CUDA) processing using a graphics processing unit (GPU). We verified that our linearization method is appropriate for applying real time imaging of SS-OCT.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.1
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• pp.62-74
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• 2002

The tracking of a reference temperature trajectory in a polymerization batch reactor is a common problem and has critical importance because the quality control of a batch reactor is usually achieved by implementing the trajectory precisely. In this study, only energy balances around a reactor are considered as a design model for control synthesis, and material balances describing concentration variations of involved components are treated as unknown disturbances, of which the effects appear as time-varying parameters in the design model. For the synthesis of a tracking controller, a method combining the input-output linearization of a time-variant system with the parameter estimation is proposed. The parameter estimation method provides parameter estimates such that the estimated outputs asymptotically follow the measured outputs in a specified way. Since other unknown external disturbances or uncertainties can be lumped into existing parameters or considered as another separate parameters, the method is useful in practices exposed to diverse uncertainties and disturbances, and the designed controller becomes robust. And the design procedure and setting of tuning parameters are simple and clear due to the resulted linear design equations. The performances and the effectiveness of the proposed method are demonstrated via simulation studies.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.410-415
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• 2013

This paper proposes a bidirectional platoon control law using a coupled distance error based on the backstepping-like feedback linearization control method for an interconnected mobile agent system with a string structure. Unlike the previous results where the single agent was controlled using the only own information without other agents, the proposed control law cannot show the only distance error convergence of each agent, but also the string stability of the whole system. Also, the control performances are improved by the proposed control law in spite of low performance of bidirectional control strategy in the previous results. The proposed bidirectional platoon control algorithm is based on the backstepping-like feedback linearization control method. The position errors between each agent and the preceding and the behind agents are coupled by weighted summation. By the proposed control law, the distance error of each agent can converge to zero while the string stability is guaranteed when the coupled errors can converge to zero. To this end, the back-stepping control method is employed. The pseudo velocity input is determined considering the kinematic relationship between agents and the string stability. Then, the actual dynamic control input is determined to make the actual velocity converge to the pseudo velocity input. The stability analysis and the simulation results of the proposed method are included in order to demonstrate the practical application of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1447-1456
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• 2011

In this paper, we propose a T-S fuzzy feedback linearization method for controlling a non-linear system with multi-input, and the method is applied for trajectory tracking control of wheeled mobile robot. First, an error dynamic equation of wheeled mobile robot is represented by a T-S fuzzy model, and then the T-S fuzzy model is transformed to a linear control system through the nonlinear fuzzy coordinate change and the nonlinear state feedback input. Simulation results showed that the trajectory tracking controller by using the proposed multi-input feedback linearization method gives better performance than the trajectory tracking controller by using the PDC(Parallel Distributed Compensation) method for controlling the T-S Fuzzy system.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.785-790
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• 2008

Vibration of a non-linear system under random parametric excitations was evaluated by probablistic methods. The non-linear characteristic terms of a system were quasi-linearized and excitation terms were remained as they were given. An analytical method where the square mean of error was minimized was ysed. An alternative method was an energy method where the damping energy and rstoring energy of the linearized system were equalized to those of the original non-linear system. The numerical results were compared with those obtained by Monte Carlo simulation. The comparison showed the results obtained by Monte Carlo simulation located between those by the analytical method and those by the energy method.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.5
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• pp.742-750
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• 1986

The lateral vibrating motion of a railway vehicle over a certain critical speed is a well known problem in the field of train dynamics. It is known that the train equations of motion are strongly coupled and highly nonlinear with the motion and causing that it is very difficult to solve the equations simultaneously. In this paper, a 8 degree of feedom model of a railway vehicle was suggested to solve the rail vehicle lateral motion. In stead of solving the nonlinear equation simultaneously, statistical linearization technique was adopted to solve those equations. The analysis results from the statistical linearization method were directly compared with those from direct nonlinear equations and found that the linearization technique can be very effective and economical for railroad vehicle analysis. By the way, it was found that the analysis results can analytically explain the intermittent hunting phenomena which has been frequently observed in experiments.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.79-90
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• 2004

Systematical robust stability analysis and design scheme for the feedback linearization control systems via fuzzy modeling are proposed. It is considered that uncertainty and disturbances are included in the Takagi-Sugeno fuzzy models representing the nonlinear plants. Robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions and by converting the analysis and design problems into the linear matrix inequality optimization, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

• International Journal of Control, Automation, and Systems
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• v.3 no.2
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• pp.225-235
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• 2005

This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.