• 전기학회논문지
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• 제60권12호
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• pp.2346-2351
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• 2011

This paper presents the intelligent external noise analysis method for nonlinear maneuvering target. After recognizing maneuvering pattern of the target by the proposed method, we track the state of the target. The external noise can be divided into mere noise and acceleration using only the measurement. divided noise passes through the filtering step and acceleration is punched into dynamic model to compensate expected states. The acceleration is the most deterministic factor to the maneuvering. By dividing, approximating, and compensating the acceleration, we can reduce the tracking error effectively. We use the fuzzy c-means (FCM) clustering as the method to divide external noise. FCM can separate the acceleration from the noise without criteria. It makes the criteria with the data made by measurement at every sampling time. So it can show the adaptive tracking result. The proposed method proceeds the tracking target simultaneously with the learning process. Thus it can apply to the online system. The proposed method shows the remarkable tracking result on the linear and nonlinear maneuvering. Finally, some examples are provided to show the feasibility of the proposed algorithm.

• 한국정밀공학회지
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• 제18권1호
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• pp.147-153
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• 2001

This paper proposes a shaker system design for acceleration test of gimbal. Main reason of shaker system design is to give acceleration to the gimbal, which is moving and tracking the target on the tracking test equipment. The shaker system is mounted on the tracking test equipment. It uses the scotch yoke mechanism to have the constant movement in return. The Scotch yoke mechanism changes the rotational movement of constant velocity to simple harmonic motion.

• Journal of Electrical Engineering and information Science
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• 제2권4호
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• pp.23-27
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• 1997

Presented are closed-form expressions of the three-state exponentially correlated acceleration (ECA) target-tracking filter. The steady-state solution is derived based on Vaughan's approach for the case that he measurements of target position and velocity are available at discrete point in time. The solution for ECA tracking filter using only position measurements and the solution for the constant acceleration (CA) tracking filter are obtained as a special case of the presented results.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.99-102
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• 2003

A new interacting multiple model (IMM) method using genetic algorithm (GA)-based intelligent input estimation(IIE) is proposed to track a maneuvering target. In the proposed method, the acceleration level for each sub-model is determined by IIE-the estimation of the unknown acceleration input by a fuzzy system using the relation between maneuvering filter residual and non-maneuvering one. The GA is utilized to optimize a fuzzy system fur a sub-model within a fixed range of acceleration input. Then, multiple models are composed of these fuzzy systems, which are optimized for different ranges of acceleration input. In computer simulation for an incoming ballistic missile, the tracking performance of the proposed method is compared with those of the input estimation(IE) technique and the adaptive interacting multiple model (AIMM) method.

• Journal of Power Electronics
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• 제12권2호
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• pp.294-304
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• 2012

This paper proposes a fuzzy speed tracking controller and a fuzzy rotor angular acceleration observer for a surface-mounted permanent magnet synchronous motor (SPMSM) based on the Takagi-Sugeno (T-S) fuzzy model. The proposed observer-based controller is robust to load torque variations since it utilizes rotor angular acceleration information instead of the load torque value. Linear matrix inequality (LMI) sufficient conditions are given to compute the gain matrices of the speed tracking controller and the observer. In addition, it is mathematically verified that the proposed observer-based control system is asymptotically stable. Simulation and experimental results are presented to confirm that the proposed control algorithm assures a better transient behavior and less sensitivity under model parameter variations than the conventional PI control method.

• Smart Structures and Systems
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• 제14권6호
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• pp.1055-1079
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• 2014

Substructure shake table testing is a class of real-time hybrid simulation (RTHS). It combines shake table tests of substructures with real-time computational simulation of the remaining part of the structure to assess dynamic response of the entire structure. Unlike in the conventional hybrid simulation, substructure shake table testing imposes acceleration compatibilities at substructure boundaries. However, acceleration tracking of shake tables is extremely challenging, and it is not possible to produce perfect acceleration tracking without time delay. If responses of the experimental substructure have high correlation with ground accelerations, response errors are inevitably induced by the erroneous input acceleration. Feeding the erroneous responses into the RTHS procedure will deteriorate the simulation results. This study presents a set of techniques to enable reliable substructure shake table testing. The developed techniques include compensation techniques for errors induced by imperfect input acceleration of shake tables, model-based actuator delay compensation with state observer, and force correction to eliminate process and measurement noises. These techniques are experimentally investigated through RTHS using a uni-axial shake table and three-story steel frame structure at the Johns Hopkins University. The simulation results showed that substructure shake table testing with the developed compensation techniques provides an accurate and reliable means to simulate the dynamic responses of the entire structure under earthquake excitations.

• 한국지능시스템학회논문지
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• 제21권4호
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• pp.469-474
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• 2011

본 논문에서는 기동표적의 위치 오차값 보상 기법을 이용한 지능형 기동표적 추적 기법을 제안한다. 기동표적의 관측값과 예상위치와의 차이를 가속도와 순수 잡음으로 분리한다. 최적의 수준으로 가속도를 추출하기 위하여 K-means 클러스터링 기법과 TS 퍼지 시스템을 이용한다. K-means 클러스터링에 의해 분리된 가속도와 잡음에 대한 소속함수를 설정하고 퍼지 모델화하여 기동표적의 특성을 파악한다. 계산상의 오차를 보상하기 위하여 분리된 가속도와 잡음은 추적 알고리즘의 계산과정에 적절히 이용된다. 추정값 계산시, 가속도를 분리 하므로써 필터링 과정은 표적의 비선형 기동을 선형기동으로 인식하여 칼만필터의 성능을 유지시킨다. 기동표적의 비선형성에 대한 오차는 추정된 가속도를 통해 보상된다. 제안된 시스템의 소속함수에 사용되는 파라미터값을 조종하여 상황에 따라 적응성과 강인성을 향상시킨다. 제안된 시스템은 실시간 추적이 가능하도록 구성하였으며, 몇 가지 예를 통하여 본 논문에서 제안한 방법의 우수성을 증명한다.

• Journal of Electrical Engineering and Technology
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• 제7권2호
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• pp.255-263
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• 2012

This paper presents the smart interacting multiple model (SIMM) using the concept of predicted point and maximum noise level. Maximum noise level means the largest value of the mere noises. We utilize the positional difference between measured point and predicted point as acceleration. Comparing this acceleration with the maximum noise level, we extract the acceleration to recognize the characteristics of the target. To estimate the acceleration, we propose an optional algorithm utilizing the proposed method and the Kalman filter (KF) selectively. Also, for increasing the effect of estimation, the weight given at each sub-filter of the interacting multiple model (IMM) structure is varying according to the rate of noise scale. All the procedures of the proposed algorithm can be implemented by an on-line system. Finally, an example is provided to show the effectiveness of the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제18권7호
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• pp.638-643
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• 2012

This paper presents an intelligent reduction method for external noise. The main idea comes from PSO-FCM (Particle Swam Optimization Fused fuzzy C-Means) clustering. The data of the target is transformed from the antenna coordinates to the vessel one and to the system coordinates. In the conversion, the overall noises hinder observer to get the exact position and velocity of the maneuvering target. While the filter is used for tracking system, unexpected acceleration becomes the main factor which makes the uncertainty. In this paper, the tracking efficiency is improved with the PSO-FCM and the compensation methodology. The acceleration is approximated from the external noise splitted by the proposed clustering method. After extracting the approximated acceleration, the rest in the noise is filtered by the filter and the compensation is added to after that. Proposed tracking method is applicable to the linear model and nonlinear one together. Also, it can do to the on-line system. Finally, some examples are provided to examine the reliability of the proposed method.

• 한국항공우주학회지
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• 제39권9호
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• pp.883-888
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• 2011

GPS를 기반으로 하는 무인항공기 추적 안테나 시스템은 일정한 주기를 가지고 위치정보를 갱신하는 특성이 있으며 이로 인하여 갱신 주기에 따른 위치 오차가 발생한다. 위치오차를 줄이기 위해 GPS의 갱신 주기를 시분할 하여 분할된 시점의 위치를 예측 하고 이를 이용하여 무인항공기를 추적할 수 있도록 하였다. 무인항공기의 위치를 예측하기 위해서 속도와 가속도 기반의 선형 칼만 필터를 사용하였으며 이를 이용하여 무인항공기의 속도와 가속도를 측정하였고 시간의 변화에 따른 위치변화를 예측한다.