• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.144-149
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• 2006

This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.11
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• pp.1621-1628
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• 2004

This paper proposes a design methodology for the robust observer using the eigenstructure assignment in multi-output systems so that the observer is less sensitive to the ill-conditioning factors such as unknown initial estimation error, modeling error and measurement bias in transient and steady-state observer performance. The robustness of the observer can be achieved by selecting the desired eigenvector matrix to have a small condition number that guarantees the small upper bound of the estimation error. So the left singular vectors of the unitary matrix spanned by space of the achievable eigenvectors are selected as a desired eigenvectors. Also, this paper proposes how to select the desired eigenvector based on the measure of observability and designs the observer with small gain. An example of a spindle drive system is simulated to validate the robustness to the ill-conditioning factors in the observer performance.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.783-789
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• 2011

Target tracking performance improvement using multi-sensor data fusion is a challenging work. However, biases in the measurements should be removed before various data fusion techniques are applied. In this paper, a bias removing algorithm using measurement data from multi-radar tracking systems is proposed and evaluated by computer simulation. To predict bias estimation performance in various geometric relations between the radar systems and target, a system observability index is proposed and tested via computer simulation results. It is also studied that target tracking which utilizes multi-sensor data fusion with bias-removed measurements results in better performance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.54-54
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• 2000

For its synergistic relationship, an integrated SDINS/GPS system has been adopted in many navigation areas. As an application of SDINS/GPS integration, the in-flight alignment process of a SDINS utilizing GPS carrier phase measurements is introduced and analyzed via an observability analysis using nul1 space method. A measurement model of double-differenced GPS carrier phase measurements is newly derived in order to be used with a SDINS error model. Also, conditions for determining the complete observability of a SDINS/GPS system are suggested and proved. Consequently, it is shown that the system is not completely observable in case of one basel me. With one baseline aligned with y-axis of body frame, pitch error and x-axis accelerometer bias are unobservable states. Also shown is that al1 states are completely observable when sequential maneuver is performed. Above results are confirmed by a covariance analysis.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.827-835
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• 1999

In this paper, a dead reckoning navigation system for differential drive mobile robots is presented. The navigation system consists of two incremental encoders and a gyroscope. We have built a third order polynomial function for compensating the nonlinear scale factor errors of the gyroscope. We utilize an indirect Kalman filter that feeds back estimated errors to the main navigation system. Also, the observability of the filter is analyzed in order to systematically evaluate the filter's performance. Experimental results show that the proposed navigation system provides a reliable position and heading angle by mutually compensating the encoder and the gyroscope errors. The proposed filter also reduces the computational burden and enhances the navigation system's reliability. The observability analysis confirms the characteristics of inevitably unbounded position error growth in dead reckoning navigation systems.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.62-67
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• 1998

Gimballed Inertial Navigation Systems(GINS) are sophisticated autonomous electro-mechanical systems which supply the position, velocity and attitude of the vehicle on which they are mounted. In order to maintain accuracy of outputs, the GINS are required to regularly calibrate senior errors. However, existing calibration methods take up a long time due to multiposition alignments needed to increase accuracy. A particular system formulation for calibration of a GINS is proposed to enhance system observability and thus to expedite calibration procedure. Performance of the proposed calibration method is compared with existing methods such as Schuler test and muliposition alignment. Simulation studies show the proposed system formulation associated with a suggested suboptimal filter is accurate as well as efficient in error identification essential to GINS calibration.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.355-359
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• 2006

For the poor observability of azimuth misalignment angle and east gyro drift rate of the traditional initial alignment, a bran-new SINS stationary fast self-alignment approach is proposed. By means of analyzing the characteristic of the strapdown inertial navigation system (SINS) stationary alignment seriously, the new approach takes full advantage of the specific force and angular velocity information given by inertial measurement unit (IMU) instead of the mechanization of SINS. Firstly, coarse alignment algorithm is presented. Secondly, a new fine alignment model for SINS stationary self-alignment is derived, and the observability of the model is analysed. Then, a modified Sage-Husa adaptive Kalman filter is introduced to estimate the misalignment angles. Finally, some computer simulation results illustrate the efficiency of the new approach and its advantages, such as higher alignment accuracy, shorter alignment time, more self-contained and less calculation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.168-171
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• 2000

This paper is concerned with fuzzy number whose values are normal, convex, upper semicontinuous and compactly supported interval in E$\_$N/ We study continuously initial observability for the following fuzzy system. x(t)=a(t)x(t)+f(t,x(t)), x(0)=x$\_$0/, y(t)=$\_$${\alpha}$/∏(x(t)), where a: [0, T]\longrightarrowE$\_$N/ is fuzzy coefficient, initial value x$\_$0/$\in$E$\_$N/ and nonlinear funtion f: [0, T]${\times}$E$\_$N/\longrightarrowE$\_$N/ satisfies a Lipschitz condition. Given fuzzy mapping ∏: C([0, T]: E$\_$N/)\longrightarrowY and Y is an another E$\_$N/.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.75-79
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• 2000

This paper proposes the optimal placement with minimum set of Phasor Measurement Units (PMU's) using tabu search and makes an alternative plan to secure the robustness of the network with PMU's. The optimal PMU Placement (OPP) problem is generally expressed as a combinatorial optimization problem subjected to the observability constraints. Thus, it is necessary to make a use of an efficient method in solving the OPP problem. In this paper, a tabu search based approach to solve efficiently this OPP problem proposed. The observability of the network with PMU's is fragile at any single PMU contingency. To overcome the fragility, an alternative scheme that makes efficient use of the existing measurement system in power system state estimation proposed. The performance of the proposed approach and the alternative scheme is evaluated with IEEE sample systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.140-148
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• 2000

This paper presents a fault detection and isolation(FDI) method based on Generalized Likelihood Ratio(GLR) test for the tightly coupled SDINS/CPS system. The GLR test is known to have the capability of detecting an assumed change while estimating its occurrence time and magnitude, and isolating the changing part. Once a fault is detected even if we don't know if the fault occurrs at either INS or GPS, multi-hypothesized GLR scheme performs the fault isolation between INS and GPS, and find which satellite malfunctions. However, in the INS faulty case, it turned out to fail to accomodate the fault isolation between accelerometer and gyroscope due to the coupling effects and a poor observability of the system. Hence, to isolate the INS fault, it needs to change the attitude of the vehicle resulting in enhancing the degree of observability.