• Journal of Institute of Control, Robotics and Systems
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• v.12 no.2
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• pp.93-100
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• 2006

In this paper, a new-type Extended Kalman Filter (EKF) is proposed as a robust nonlinear filter for a stochastic nonlinear system. The original EKF is widely used for various nonlinear system applications. But it is fragile to its estimation errors because they give rise to linearization errors that affect the system mode1 as the modeling errors. The linearization errors are nonlinear functions of the estimation errors therefore it is very difficult to obtain the accurate error covariance of the EKF using the linear form. The inaccurately estimated error covariance hinders the EKF from being a sub-optimal estimator. The proposed filter tries to obtain the upper bound of the error covariance tolerating the uncertainty of the error covariance instead of trying to obtain the accurate one. It treats the linearization errors as uncertain modeling errors that can be handled by the robust linear filtering. In order to be more robust to the estimation errors than the original EKF, the proposed filter minimizes the upper bound like the robust linear filter that is applied to the linear model with uncertainty. The in-flight alignment problem of the inertial navigation system with GPS position measurements is a good example that the proposed robust filter is applicable to. The simulation results show the efficiency of the proposed filter in the robustness to initial estimation errors of the filter.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.11
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• pp.760-767
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• 2004

In this paper, we propose sufficient conditions under which nonlinear systems can be transformed into nonlinear observer canonical form in the extended state space by virtue of dynamic system extension. The proposed scheme weakens two major restrictions of observer error linearization technique. Once a nonlinear system is transformed into nonlinear observer canonical form using dynamic system extension, a state observer can be easily designed. Two illustrative examples are included in order to compare the proposed scheme and observer error linearization method.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.448-452
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• 2001

This paper describes the nonlinear sensorless control of induction motor by using feedback linearization and current error; the feedback linearization technique and the current error are applied for independent between rotor flux and electric torque and for speed estimation. The dynamic characteristics of the proposed nonlinear control algorithm involving field weakening area are verified by simulation and experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1176-1181
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• 2010

This paper proposes three positioning algorithms using TOA measurements: 1) The well-known linearization method using Taylor series, 2) a modified Savarese method considering measurement noise, which does not need linearization, and 3) a modified Bancroft method where TOA measurements instead of pseudorange measurements are considered. Furthermore, through an error analysis, for Savarese method, divergence of altitude is anticipated if the transmitters are located at the same height. To prevent height divergence, the Savarese method is modified again for receivers which assumed moving on the even plane. Error analysis also shows the relationship between Bancroft and Savarese method. From the analysis it is expected that the performance of Savarese method is worse than Bancroft method because of error amplification during difference operation. Experiments using real TOA measurement from the time difference of ultra sound and RF validate the proposed methods and show that analysis is correct.

• 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.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.72-76
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• 1990

A new statistical linearization technique for nonlinear system called covariance matching method is proposed in this paper. The covariance matching method makes the mean and variance of an approximated output be identical real functional output, and the distribution of the approximated output have identical shape with a given random input. Also, the covariance matching method can be easily implemented for statistical analysis of nonlinear systems with a combination of linear system covariance analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.2
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• pp.138-145
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• 2001

Measurement errors in a digital measurement systems are mainly due to the consisting elements accuracies and the circuit parameters changes following the environment variations such as temperature. Further, systems non-linearity makes the measurement accuracy worse, and accordingly a linearization method should be considered to avoid this worsening. In this study, a temperature error-correction method and linearization methods are proposed and a digital temperature measurement system utilizing these methods is realized. And the proposed measurement methods are observed to increase the measurement accuracy of the digital measurement system.

• 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 Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.558-564
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• 2008

This paper presents an approach to combine adaptive controller with feedback linearization, which extends the applicability of the adaptive controller to a wider class of systems. The adaptive controller guarantees the asymptotic tracking convergence and the transient performance of the tracking error. The feedback linearization transforms a nonlinear plant into a linear time invariant form. The asymptotic tracking convergence is shown by the use of Lyapunov stability analysis and Barbalat's lemma.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.479-483
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• 2006

Indoor positioning is recently highlighted and various kinds of indoor positioning systems are under developments. Since positioning systems have their own characteristics, proper positioning scheme should be chosen according to the required specifications. Positioning methods are often classified into time-based and angle-based one, and this paper presents the error analysis of these location methods. Because measurement equations of these methods are nonlinear, linearization is usually needed to get the position estimate. In this paper, Gauss-Newton method is used in the linearization. To analyze the position error, we investigate the error ellipse parameters that include eccentricity, rotation angle, and the size of ellipse. Simulation results show that the major axes of error ellipses of TOA and AOA method lie in different quadrants at most region of workspace, especially where the geometry is poor. When the TOA/AOA hybrid scheme is employed, it is found that the error ellipse is reduced to the intersection of ellipses of TOA and AOA method.