• 반도체디스플레이기술학회지
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• 제9권2호
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• pp.41-47
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• 2010

In this paper we suggest an improvement upon the previous method of estimating a body's attitude. This paper presents a method that overcomes the shortcomings of previous studies. Applying the method of separating the acceleration of gravity component from the accelerometer's output improves the performance of the attitude estimation and extends the scope. In order to apply the method of the attitude estimation in an actively moving body, a new acceleration value containing the acceleration of gravity is calculated. This paper also proposes the method which minimizes the estimation error in estimating the moving body's attitude which is changing rapidly. Finally, this paper suggests a method that detects the gyroscope's drift and compensates for this drift using accelerometer. Applying the method improves the performance of the attitude estimation.

• 전력전자학회논문지
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• 제24권1호
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• pp.33-39
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• 2019

We propose a mechanical parameter estimation algorithm for surface-mounted permanent magnet synchronous motors (SPMSMs) using a sliding-mode observer (SMO) and an adaptive filter. The SMO estimates system disturbances in real time, which contain the information on mechanical parameters. A desirable feature that distinguishes the proposed estimation algorithm from other existing mechanical parameter estimators is that the adaptive filter estimates electromagnetic torque to improve the estimation performance. Moreover, the SMO acts as a low-pass filter to suppress the chattering effect, which enables the smooth output signals of the SMO. We verify the mechanical parameter estimation performance for SPMSM by conducting extensive experiments for the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.386-391
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• 2003

This paper focuses on robust $H_{\infty}$ control for bilinear systems with time-varying parameter uncertainties and exogenous disturbance via output feedback. $H_{\infty}$ control is achieved via separation into a $H_{\infty}$ state feedback control problem and a $H_{\infty}$ state estimation problem. The suitable robust stabilizing output feedback control law can be constructed in term of approximated solution to x-dependent Riccati equation using successive approximation technique. Also, the $H_{\infty}$ filter gain can be constructed in term of solution to algebraic Riccati equation. The output feedback control robustly stabilizes the plant and guarantees a robust $H_{\infty}$ performance for the closed-loop systems in the face of parameter uncertainties and exogenous disturbance.

• 경영과학
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• 제15권2호
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• pp.125-142
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• 1998

The aggregation on linear large-scale dynamic systems is examined in this paper and a "two-step" approach is proposed. In this procedure, the aggregated system consists of two subsystems. The first subsystem represents aggregation through the retainment of dominant eigenvalues of the original system, leading to a first approximation of the desired output of the original system. The purpose of augmenting it with a second subsystem is to provide an estimation of the error on the first approximation, thus permitting a second correction to the output approximation and resulting in an output approximation of greater accuracy. Optimization techniques are discussed for the determination of unknown parameters in the aggregated system. These techniques use minimization principles of certain suitable performance indices and are developed for both single input-single output and multiple input-multiple output system. Numerical examples illustrating these procedures are given and the results are compared with those obtained using existing methods. Finally, a pharmacokinetics problem is studied from the aggregation point of view.

• 한국통신학회논문지
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• 제21권3호
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• pp.747-752
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• 1996

In this paper, we propose a new SO-MLSE(soft-output maximum likelihood sequence estimation) equalizer, which can be used in GSM digital cellular system) it uses complex correlation of training sequence to obtain the channel information and the equalization is performed by MLSE using Viterbi algorithm. In order to generate a soft-decision input to channel decoder (Viterbi decoder), the soft-output equalization algorithm is needed. The adopted algorithm doesn't require to modify the structure of HO-MLSE(hard output MLSE) equalizer, that is, SO-MLSE equalizer can be implemented by adding soft-output generation block to HO-MLSE equalizer. This algorithm uses the outputs of matched filter and HO-MLSE equalizer. It turns out that the complexity of proposed SO-MLSE equalizer is simpler than those of other SO-MLSE equalizer and its perforance is almost the same as those of others. Finally, the proposed SO-MLSE equalizer is also implemented s a prototype with ADSP-2101 16-bits fixed point digital signal processing chip.

• International Journal of Internet, Broadcasting and Communication
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• 제12권3호
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• pp.1-8
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• 2020

This paper studied a method of estimating target information using a radar in wireless communication. Position information on the target can be estimated angle, distance and velocity. The velocity information can be estimated since the Doppler frequency is changed in the moving target. The signal incident on the receiving array antenna is multiplied by the delay time and the reference signal to represent the output signal. This output signal is estimated by applying FFT (Fast Fourier Transform) after calculating signal correlation through correlation integrator. Since the output signal must be calculated within the correlator, it should be processed with the Dwell time. The correlation signal of the correlation integrator outside this Dwell time is indicated by the velocity measurement error. The FFT is applied to the signal that has passed through the correlated integrator in order to estimate the distance of the signal. The Doppler resolution must be improved because the FFT estimates target information using the Doppler information. The Doppler resolution decreases with increasing the integration time. The velocity information estimation should have no spread of the velocity. As a result of the simulation, there was no spread of the target velocity in this study.

• 한국소음진동공학회논문집
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• 제14권3호
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• pp.208-213
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• 2004

This paper is concerned with the theoretical estimation of the single-input single-output(SISO) positive position feedback(PPF) controller and the derivation of the stability conditions for the multi-input multi-output (MIMO) PPF controller. Although the stability condition for the SISO PPF controller was derived in the earlier works, the question regarding the performance estimation of the SISO PPF controller has never been studied theoretically. Hence, the SISO PPF controller for the single degree-of-freedom system was first investigated and then control parameters including gain, the filter frequency, and the damping factor of the PPF controller were analyzed in detail thus providing the design methodology for the SISO PPF controller. In the case of real structure. there are infinite number of natural modes so that some modes are to be controlled by a limited number of actuator and sensor. Based on the theoretical results on the SISO PPF controller, the stability condition for the multi-input multi-output PPF controller was derived when only the few number of modes are to be controlled. The control spillover problem is also discussed in detail.

• Journal of Power Electronics
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• 제9권4호
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• pp.654-666
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• 2009

Direct torque control (DTC) of induction machines (IM) is a well-known strategy of these drives control which has a fast dynamic and a good tracking response. In this paper a nonlinear DTC of speed sensorless IM drives is presented which is based on input-output feedback linearization control theory. The IM model includes iron losses using a speed dependent shunt resistance which is determined through some effective experiments. A stator flux vector is estimated through a simple integrator based on stator voltage equations in the stationary frame. A novel method is introduced for DC offset compensation which is a major problem of AC machines, especially at low speeds. Rotor speed is also determined using a rotor flux sliding-mode (SM) observer which is capable of rotor flux space vector and rotor speed simultaneous estimation. In addition, stator and rotor resistances are estimated using a simple but effective recursive least squares (RLS) method combined with the so-called SM observer. The proposed control idea is experimentally implemented in real time using a FPGA board synchronized with a personal computer (PC). Simulation and experimental results are presented to show the capability and validity of the proposed control method.

• 한국기계가공학회지
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• 제15권2호
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• pp.131-138
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• 2016

In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.91-94
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• 1996

This paper presents an approach to estimation of learning gain in iterative learning control for discrete-time affine nonlinear systems. In iterative learning control, to determine learning gain satisfying the convergence condition, we have to know the system model. In the proposed method, the input-output equation of a system is identified by neural network refered to as Piecewise Linearly Trained Network (PLTN). Then from the input-output equation, the learning gain in iterative learning law is estimated. The validity of our method is demonstrated by simulations.