• 대한임베디드공학회논문지
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• 제3권2호
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• pp.102-108
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• 2008

This paper describes a mapping and localization based on wave algorithm[11] and Kalman filter for effective SLAM. Each robot in a multi robot system has its own task such as building a map for its local position. By combining their data into a shared map, the robot scans actively seek to verify their relative locations. For simultaneous localization the algorithm which is well known as Kalman Filter (KF) is used. For modelling the robot position we wish to know three parameters (x, y coordinates and its orientation) which can be combined into a vector called a state variable vector. The Kalman Filter is a smart way to integrate measurement data into an estimate by recognizing that measurements are noisy and that sometimes they should ignored or have only a small effect on the state estimate. In addition to an estimate of the state variable vector, the algorithm provides an estimate of the state variable vector uncertainty i.e. how confident the estimate is, given the value for the amount of error in it.

• 대한전자공학회논문지
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• 제24권4호
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• pp.597-602
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• 1987

In this paper, an adaptive observe based upon the exponentially weighted least-squares method is implemented in the design of a model reference adaptive controller for an unknown time-invariant discrete single-input single-output linear plant. A method of selecting the state variable filter is proposed. In this scheme, all the past data are weithted exponentially with the weighting coefficient.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.53.6-53
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• 2001

In this paper, we are concerned with a tracking filter algorithm which can track a maneuvering target. Among the novel tracking filter algorithms, the input estimation (IE) filter can be summarized as estimating the unknown maneuver input and compensating the state according to the estimated input, and the variable dimension filter (VDF) can be summarized as detecting the maneuver of target and changing the dimension of the target dynamics to accomodate the maneuver of target They have some goods and bads with respect to each other. The variable dimension filter with input estimation (VDIEF) is constructed by combining the two filtering algorithms. However, it requires too much computational burden while it has good performance. We propose another variable dimension with input estimation ...

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.262-264
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• 2005

We propose a filter design method to suppress the effect of gyroscope mixed random errors at INS system level. It is based on the result that mixed random errors can be represented by a single equivalent ARMA model. At first step, the time difference of equivalent ARMA process is performed, which consider the characteristic of indirect feedback Kalman filter used in INS filter. Next, a state space conversion of time differenced ARMA model is achieved. If the order of AR is greater than that of MA, the controllable or observable canonical form is used. Otherwise, we introduce the state equation of which the state variable is composed of the ARMA model output and several step ahead predicts of that. At final step, a complete form state equation is presented. The simulation results shows that the proposed method gives less transient error and better convergence compared to the conventional filter which assume the mixed random errors as white noise.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
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• pp.119-121
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• 2005

The sliding-mode control technique could make a system unstable which external disturbance and uncertainty exists in. This paper suggests a robust sliding-mode control algorithm which can be applied to a linear system with parameter uncertainties. To reduce the chattering effect, the whole system is comprised of using a state variable in which the state's estimated value is added. The condition of estimated state results from state observer. The proposed control algorithm uses the optimal feedback controller following the dynamic system equation which consists of a state variable resulting from its own state variable, controller input, estimated state variable. Through comparison with the time optimal control algorithm using simulation, the suggested algorithm shows the improved stability and robustness while it manifests the fast tracking characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.561-564
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• 2004

This paper proposes a new application of Kalman filter to estimate speed sensorless DC motor. Kalman filter can estimate the system state variables accurately; even the system input is disturbed with noise. In the design, the mathematical model of DC motor in discrete state-space form will be created; the speed of DC motor which is considered as state variable and can be estimated by using Kalman filter. In the experiment; TMS320C31 floating point digital signal processor is used for hardware implementation, the input is disturbed with/and without white noise in the experiment. The experimental results show the speed of DC motor which is estimated by Kalman filter has good accuracy when compared with the results from tacho-meter.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1986년도 하계학술대회논문집
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• pp.140-144
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• 1986

In this paper an FIR(finite impulse response) filter and smoother are introduced for discrete time-invariant state-space models with driving noises. The FIR structure not only quarantees the BIBO stability and the robustness to parameter changes but also improves the filter divergence problem. It is shown that the impulse responses of the FIR filter and the smoother are obtained by Riccati-type difference equations and that they are to be time-invariant and reduced to very simple forms. For implementational purpose, recursive forms of the FIR filler and smoother are derived with each other used as the adjoint variable.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.937-940
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• 1995

The purpose of this paper is to present a nonlinear system identification method, where an adaptive nonlinear recursive state-spare(ANRSS) filter is employed as its filter structure, and a variable step (VS) algorithm is applied as its adaptation law. To demonstrate the validity of the proposed method, some simulation results are included.

• 대한전자공학회논문지SP
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• 제46권1호
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• pp.104-110
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• 2009

본 논문에서는 가변 스텝사이즈를 사용하는 SAP 적응필터의 구현을 위한 파이프라인 구조를 적용한 새로운 알고리즘을 제안한다. 제안 기법에서는 SAP 적응필터를 부밴드로 충분히 분해함으로써 단순화된 SAP적응필터를 유도할 수 있으며, 적응부필터들의 계수들을 역행렬 연산 없이 간단한 식으로 갱신할 수 있다. 단순화된 SAP 적응 필터의 수렴속도와 정상상태토차는 가변스텝사이즈를 사용함으로서 개선한다. 실제 구현을 위해 단순화된 SAP 적응필터는 파이프라인 기법을 사용하여 변환된다.

• 한국항공우주학회지
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• 제34권4호
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• pp.47-52
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• 2006

불규칙 혼합잡음의 등가 ARMA 모델 표현을 사용하여 자이로의 불규칙 혼합잡음을 고려하는 보조항법시스템 칼만필터 설계 방법을 제안한다. 필터 설계 절차는 먼저 보조항법 시스템에 사용되는 필터는 간접 되먹임 칼만필터임을 고려하여 등가 ARMA 모델로 표현된 자이로 불규칙 잡음의 시간 차분을 구한다. 다음으로 시간 차분된 ARMA 모델을 상태 방정식으로 표현하는데 AR과 MA 차수에 따라 두 가지로 나누어진다. 먼저 AR 차수가 큰 경우 가제어 혹은 가관측 특이형태를 사용한다. MA 차수가 큰 경우에는 몇 단계 이후의 예측치를 상태변수로 하는 상태방정식을 사용하는데, 이때 자이로 출력을 보상하는 값에 따라 다시 고차수 필터와 저차수 필터로 구분된다. 마지막으로 자이로 불규칙 잡음을 보조항법시스템 칼만필터에 포함시켜 최종적인 필터 모델을 얻는다. 시뮬레이션 결과를 통하여 제안된 고차수 및 저차수 필터 모두 혼합잡음을 백색잡음으로 간주한 기존의 필터보다 항법오차를 감소시킬 수 있음을 보임으로써 그 효용성을 제시한다.