• Smart Structures and Systems
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• v.7 no.3
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.7
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• pp.547-555
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• 2002

This paper proposes a stabilizing controller for the multirate sampled-data systems, which have a periodic output measurement scheme, in case of the open-loop unstable plant. A sufficient condition for maintaining observability in the multirate sampled-data systems is derived and a design strategy for filtered disturbance rejection is proposed. We also propose a design method for the plant output estimator. It is shown that the proposed pre-stabilizing controllers can stabilize the plant through the simulations. The proposed controller has IMC structure, and can be decomposed into the pre-stabilizing controller, the plant output estimator, the filtered disturbance estimator and the inverse of the fast pre-stabilized plant model. We assume that the plant is open-loop unstable and the disturbance consists of a sum of finite number of sinusoids with different frequencies. Some examples are presented for illustrations.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.2
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• pp.99-107
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• 2003

This paper proposes a design for testability (DFT) and testability analysis method for register-transfer level (RTL) circuits. The proposed method executes testability analysis - controllability and observability - on the RTL circuit and determines the insertion points to enhance the testability. Then with the associated priority based on the testability, we insert only a few of the test multiplexers resulting in minimized area overhead. Experimental results shows a higher fault coverage and a shorter test generation time than the scan method. Also, the proposed method takes a shorter test application time required.

• ETRI Journal
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• v.34 no.1
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• pp.44-54
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• 2012

Because of the intrinsic lack of internal-system observability and controllability in highly integrated multicore processors, very restricted access is allowed for the debugging of erroneous chip behavior. Therefore, the building of an efficient debug function is an important consideration in the design of multicore processors. In this paper, we propose a flexible on-chip debug architecture that embeds a special logic supporting the debug functionality in the multicore processor. It is designed to support run-stop-type debug functions that can halt and control the execution of the multicore processor at breakpoint events and inspect the possible causes of any errors. The debug architecture consists of the following three functional components: the core debug support block, the multicore debug support block, and the debug interface and control block. By embedding this debug infrastructure, the embedded processor cores within the multicore processor can be debugged simultaneously as well as independently. The debug control is performed by employing a JTAG-based scanning operation. We apply this on-chip debug architecture to build a debugger for a prototype multicore processor and demonstrate the validity and scalability of our approach.

• Journal of Ocean Engineering and Technology
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• v.22 no.4
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• pp.106-113
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• 2008

This paper presents an underwater navigation system based on range measurements from a known reference station fixed on the sea bottom or floated at surface with a buoy, for which the system is extended to 3-dimensional coordinates. We formulated a state equation in polar coordinates and constituted an extended Kalman filter for discrete-time implementation of the navigation algorithm. The autonomous underwater vehicle, lSiMl, cruising with a constant speed can estimate its trajectory using just range measurements and additional depth, heading and pitch sensors. Simulation studies were performed to evaluate the underwater navigation of the maneuvering AUV with range measurements. We modulated the sample rate of range measurements to evaluate the effect of the update rate, and changed the initial position error of the AUV to check the robustness to estimation errors. Simulation results illustrates that the extended navigation system provides convergence of the state estimates. The navigation system was conditionally stable when it had initial position errors.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.536-542
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• 2016

To enhance tracking efficiency, a target-tracking filter with a resource management algorithm is required. One of the resource management algorithms chooses or evaluates the proper sampling time using cost functions which are related to the target tracking filter. We propose a resource management algorithm for bearing only tracking environments. Since the tracking performance depends on the system observability, the bearing-only tracking is one of challenging target-tracking fields. The proposed algorithm provides the adaptive sampling time using the variation rate of the error covariance matrix from the target-tracking filter. The simulation verifies the efficiency performance of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.186-186
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• 2000

In the GPS/DR integrated system, the GPS position(or velocity) is used to compensate the DR output and to calibrate errors in the DR sensor. This synergistic relationship ensures that the calibrated DR accuracy can be maintained even when the GPS signal is blocked. Because of the observability problem, however, the DR sensors are not sufficiently calibrated when the vehicle speed is low. This problem can be solved if we use a multi-antenna GPS receiver for attitude determination instead of conventional one. This paper designs a two-antenna GPS receiver integrated with DR sensors. The proposed integration system has three remarkable features. First, the DR sensor can be calibrated regardless of the vehicle speed with the aid of two-antenna GPS receiver. Secondly, the search space of integer ambiguities in GPS carrier-phase measurements is reduced to a part of the surface of the sphere using DR heading. Thirdly, the detection resolution of cycle-slips in GPS carrier-phase measurements is improved with the aid of DR heading. From the experimental result, it is shown that the search grace is drastically reduced to about 3120 of the non-aided case and the cycle-slips of 1 or half cycle can be detected.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.285-294
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• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05a
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• pp.117-120
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• 2002

Electrical power system has very complexity problem that it is plan measurement system to achieve Harmonic State Estimation (HSE). This complexity problem depends on discord of necessary accuracy, certainty of noise that exist in data communication damage and converter, adaptability of network modification and minimum of expense size of system, estimated monitering. Also, quantity of available measurement equipment for harmonic measurement has been limited. Therefore, systematic method that choose measurement location for harmonic state estimation. This paper is that see proposed HSE that use Observability Analysis(OA) for harmonic state estimation of electrical power system. OA depends on measurement number, measurement location and measurement form here, it is analysis method that depend on network form and admittance of the system. OA used achieve harmonic state estimation that it is Applied to New Zealand electrical power system to prove validity of HSE algorithm that propose. This study result about harmonic state estimation of electrical power system displayed very economical and effective method by OA.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.10
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• pp.843-848
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• 2001

Most of gimballed inertial navigation systems(GNIS) are calibrated periodically to maintain their inherent accuracy. The existing calibration techniques using the conventional schuler test with the least square method and the multiposition test take a long time and have some problems in procedures. To solve this problem, calibration method using a linear Kalman filter is proposed by us. In this paper, the calibration method by the change of Schuler period is studied in order to improve the calibration performance of the gimballed INS. First of all, it is shown that the observability of Kalman filter is also enhanced the Schuler period is decreased. Simulation results show that the calibration performance using the present scheme is improved according to the decrease of the Schuler period and the calibration time is shortened extremely, too. And our proposed technique shows desirable estimation performance for the g-sensitive errors of inertial sensors in particular.