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Identification of Continuous-Time Low-Order models via Weighted Moments |
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SeungPyo Cha(Chungbuk National University, Korea), JongGeon Lee(Agency for Defense Development, Korea), Young Chol Kim(Chungbuk National University, Korea) |
| This paper presents an identification algorithm for continuous-time low-order models both with delays and free of delays via weighted time moments. In this approach, it is sufficient to obtain response data stimulated by a single pulse, such as a rectangular or a half-sine pulse. From the weighted moments of both input and output data, the parameters of low-order transfer function models are determined by solving linear equations in a matrix form. Numerical examples show that the algorithm provides robust identification results. |
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Prediction Impulsive Observer for Sampled Data Linear Systems |
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Atif Qayyum(National University of Sciences and Technology, Pakistan) |
| This paper introduces the novel idea of using a prediction type impulsive observer for sampled-data linear time invariant systems. After the successful introduction of the current impulsive observer, this new technique is a logical extension as existing in the case of discrete systems. Despite having only discrete output measurements at the sampling points, the continuous states of the plant are estimated. The proposed estimation is able to achieve deadbeat convergence for any non-pathological sampling time. The approach is simulated through a numerical example for its efficacy. |
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Model based Real-Time Flow Rate Estimation in Open Channels with Application to Conventional Drilling |
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Asanthi Jinasena, Roshan Sharma(University of South-Eastern Norway, Norway) |
| Improvements in kick/loss detection are a main interest in the drilling industry. Advanced online return flow sensors play a vital role here. In this paper, the use of a Venturi channel in the return flow line, which can be developed as an online soft sensor is proposed. A reduced order mathematical model is used for flow rate estimation. Different estimators (a linear observer, Kalman filters) are tested. The estimations are well comparable with the experimental data. The proposed system shows a good potential of developing into an online soft sensor in kick/loss detection algorithms. |
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A filtered-x optimal step-size-NSAF active noise cancellation algorithm robust to impulse noise with step-size scaler |
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Taesu Park, Dongwoo Kim, PooGyeon Park(Pohang University of Science and Technology, Korea) |
| This paper proposes an algorithm which controls the noise ctively with a variable step-size normalized subband adaptive filter VSS-NSAF). One of the difficulties of active noise control (ANC) system is that the system coefficients is very long because of their long echo tails. Due to the long filter coefficients of the ANC system, NSAF algorithm is applied to reduce the computational complexity. Also the step size scaler is applied to restrain rong coefficient update by impulsive noise from target point. The step size scaler makes the step size of VSS-NSAF algorithm very small when impulsive |
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