• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1667-1671
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• 2003

A computer program to calculate properties of nitrogen is developed. Procedures for the calculation is briefly discussed. The program calculates unknown thermodynamic properties fixing the state with two independent input properties. If input value by user is inappropriate, it displays an error message and replaces the input value with an appropriate one. In addition user can change units with easy. The program developed in this work can be utilized to calculate parameters required for the simulation and design of an equipment using nitrogen.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.101-106
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• 1990

The problem of constructing an observer for use in the control of superheater temperature with desuperheater is considered. The distributed heat input into the superheater is usually not available for use in the observer, and hence is treated as a disturbance. The observer theory for systems with unknown inputs is exploited and applied to the problem. Approximation of the heat input utilizing the specific heat input distribution pattern is also considered.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.117-126
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• 2003

This paper proposes a real-time application of Walsh functions which is based on the on-line Walsh transformation and on-line Walsh function's differential operation. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of Walsh transformation to overcome this shortcoming. And the proposed method apply to the unknown inputs observer(UIO) design for linear time-invariant dynamical systems

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.2
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• pp.16-24
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• 2010

This paper is proposed a novel fuzzy disturbance observer based on backstepping method for nonlinear systems with unknown disturbance. Using fuzzy logic systems, a fuzzy disturbance observer with the disturbance observation input is introduced for unknown disturbance. To guarantee that the proposed disturbance observer estimates the unknown disturbance, the disturbance observation error dynamic system is employed. Under the framework of the backstepping design, the fuzzy disturbance observer is constructed recursively and an adaptive laws and the disturbance observation input are derived. Numerical examples are given to demonstrate the validity of our proposed disturbance observer for nonlinear systems.

• Smart Media Journal
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• v.13 no.8
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• pp.16-25
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• 2024

Recently, there has been a growing emphasis on identifying both known and unknown diseases in plant disease recognition. In this task, a model trained only on images of known classes is required to classify an input image into either one of the known classes or into an unknown class. Consequently, the capability to recognize unknown diseases is critical for model deployment. To enhance this capability, we are considering three factors. Firstly, we propose a new logits-based scoring function for unknown scores. Secondly, initial experiments indicate that a compact feature space is crucial for the effectiveness of logits-based methods, leading us to employ the AM-Softmax loss instead of Cross-entropy loss during training. Thirdly, drawing inspiration from the efficacy of transfer learning, we utilize a large plant-relevant dataset, PlantCLEF2022, for pre-training a model. The experimental results suggest that our method outperforms current algorithms. Specifically, our method achieved a performance of 97.90 CSA, 91.77 AUROC, and 90.63 OSCR with the ResNet50 model and a performance of 98.28 CSA, 92.05 AUROC, and 91.12 OSCR with the ConvNext base model. We believe that our study will contribute to the community.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1278-1282
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• 2003

A new interacting multiple model (IMM) method using 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 genetic algorithm (GA) is utilized to optimize a fuzzy system for 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 the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.73-82
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• 1996

In this paper, an efficient algorithm for recognizing and positioning occuluded objects in a two-dimensional plane is presented. Model objects and unknown input image are approximated by polygonal boundaries, which are compactly represented by shape functions of the polygons. The input image is partitioned into measningful segments whose end points are at the locations of possible occlusion - i.e. at concave vertices. Each segment is matched against known model objects by calculating a matching measure, which is defined as the minimum euclidean distance between the shape functions. An O(mm(n+m) algorithm for computing the measure is presentd, where n and m are the number of veritces for a model and an unknown object, respectively. Match results from aprtial segments are combined based on mutual compatibility, then are verified using distance transformation and translation vector to produce the final recognition. The proposed algorithm is invariant under translation and rotation of objects, which has been shown by experimental results.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.7
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• pp.133-139
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• 1996

전형적인 상태 관측기에서는, 외란이 시스템 입력에 가해지는 경우 시스템의 상태 추정이 불가능하다. 이러한 상태관측 문제에 대한 한가지 대책법으로서 비례적분(PI) 관측기가 제안되어 스텝외란의 소거에 대한 유효성이 밝혀져 로바스트 제어기 설계에 대한 응용으로서 널리 연구가 행해져 왔다. 그러나, 미지입력에 대한 PE 관측기 설계는 여전히 문제로 남아 있다. 이 논문에서는 미지입력 PI 관측기의 설계법을 제안하고, 이에 대한 응용으로서 완전 LTR을 실현할 수 있는 결과를 보인다. 먼저, 입력의 정보없이 시스템의 상태를 추정할 수 있는 미지입력 PI 관측기의 충분조건을 제안하고, PE 관측기의 설계에 요구되는 필요충분조건을 보인다. 이러한 조건은 완전 LTR의 실현을 위한 직접적인 요구조건임을 보인다. 따라서, 완전 LTR을 달성하면서 지정한 관측기의 극을 지니는 PI 관측기 설계가 가능하다.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.665-667
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• 1999

An adaptive algorithm is presented for diagnosis of actuator faults. The concept of unknown input decoupling is combined with an adaptive observer, leading to an adaptive diagnostic observer, which has the robustness property in the presence of an unmeasurable term such as uncertainties. The observation error equation for the adaptive diagnostic observer does not depend on the effect of uncertainties and used to construct an adaptive diagnostic algorithm that provides the estimates of the gains of actuators, which can be obtained directly via the use of the augmented error technique. The simulation results indicate that the proposed algorithm is more realistic in the sense that better robustness properties can be assured without knowledge about uncertainties and is potentially useful in the development of a fault tolerant control system.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2182-2184
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• 2004

This paper presents a systematic and straightforward fault estimation approach for process fault detection. isolation and accommodation. The approach includes the design of a reduced-order observer and an algebraic-fault estimator. The observer is designed for an unknown input and fault-free system, which is obtained by coordinate transformations of original systems with unknown inputs and faults. The observer information is devoted to- the fault estimation for fault detection and isolation. The fault estimates can be used to form an additional control input to accommodate the fault. The suggested scheme is verified through simulation studies performed on the control of a vertical takeoff and landing (VTOL) aircraft in the vertical plane.