• 한국산림과학회지
• /
• 제67권1호
• /
• pp.52-59
• /
• 1984

A Gentan probability q(j) is the probability that a newly planted forest will be felled at age-class j. A future change in growing stock and yield of the forests can be predicted by means of this probability. On the other hand a state of the forests is described in terms of an n-vector whose components are the areas of each age-class. This vector, called age-class vector, flows in a n-1 dimensional simplex by means of $n{\times}n$ matrices, whose components are the age-class transition probabilities derived from the Gentan probabilities. In the simplex there exists a fixed point, into which an arbitrary forest age vector sinks. Theoretically this point means a normal state of the forest. To each age-class-transition matrix there corresponds a single normal state; this means that there are infinitely many normal states of the forests.

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

• Journal of Astronomy and Space Sciences
• /
• 제29권3호
• /
• pp.287-293
• /
• 2012

Satellite operating agencies are constantly monitoring conjunctions between satellites and space objects. Two line element (TLE) data, published by the Joint Space Operations Center of the United States Strategic Command, are available as raw data for a preliminary analysis of initial conjunction with a space object without any orbital information. However, there exist several sorts of uncertainties in the TLE data. In this paper, we suggest and analyze a method for estimating the uncertainties in the TLE data through mean, standard deviation of state vector residuals and covariance matrix. Also the estimation results are compared with actual results of orbit determination to validate the estimation method. Characteristics of the state vector residuals depending on the orbital elements are examined by applying the analysis to several satellites in various orbits. Main source of difference between the covariance matrices are also analyzed by comparing the matrices. Particularly, for the Korea Multi-Purpose Satellite-2, we examine the characteristics of the residual variation of state vector and covariance matrix depending on the orbital elements. It is confirmed that a realistic consideration on the space situation of space objects is possible using information from the analysis of mean, standard deviation of the state vector residuals of TLE and covariance matrix.

• Smart Structures and Systems
• /
• 제15권1호
• /
• pp.57-80
• /
• 2015

Extended Kalman Filter (EKF) has been widely used for structural identification and damage detection. However, conventional EKF approaches require that external excitations are measured. Also, in the conventional EKF, unknown structural parameters are included as an augmented vector in forming the extended state vector. Hence the sizes of extended state vector and state equation are quite large, which suffers from not only large computational effort but also convergence problem for the identification of a large number of unknown parameters. Moreover, such approaches are not suitable for intelligent structural damage detection due to the limited computational power and storage capacities of smart sensors. In this paper, a two-stage and two-step algorithm is proposed for the identification of structural damage as well as unknown external excitations. In stage-one, structural state vector and unknown structural parameters are recursively estimated in a two-step Kalman estimator approach. Then, the unknown external excitations are estimated sequentially by least-squares estimation in stage-two. Therefore, the number of unknown variables to be estimated in each step is reduced and the identification of structural system and unknown excitation are conducted sequentially, which simplify the identification problem and reduces computational efforts significantly. Both numerical simulation examples and lab experimental tests are used to validate the proposed algorithm for the identification of structural damage as well as unknown excitations for structural health monitoring.

• Structural Engineering and Mechanics
• /
• 제2권2호
• /
• pp.125-139
• /
• 1994

A vector algorithm for calculating the stiffness matrices of reinforced concrete shell elements is presented. The algorithm is based on establishing vector lengths equal to the number of elements. The computational efficiency of the proposed algorithm is assessed on a Cray Y-MP supercomputer. It is shown that the vector algorithm achieves scalar-to-vector speedup of 1.7 to 7.6 on three moderate sized inelastic problems.

• 한국환경과학회지
• /
• 제16권12호
• /
• pp.1319-1324
• /
• 2007

A tank model in conjunction with Kalman filter is developed for prediction of sediment yield from an upland watershed in Northwestern Mississippi. The state vector of the system model represents the parameters of the tank model. The initial values of the state vector were estimated by trial and error. The sediment yield of each tank is computed by multiplying the total sediment yield by the sediment yield coefficient. The sediment concentration of the first tank is computed from its storage and the sediment concentration distribution(SCD); the sediment concentration of the next lower tank is obtained by its storage and the sediment infiltration of the upper tank; and so on. The sediment yield computed by the tank model using Kalman filter was in good agreement with the observed sediment yield and was more accurate than the sediment yield computed by the tank model.

• 한국통신학회논문지
• /
• 제23권9A호
• /
• pp.2372-2382
• /
• 1998

In this paper, we propose a new edge based finite state vector quantization method having better performance than conventional side-match finite state vector quantization. In our proposed scheme, each dCT transformed block is classified to 17 classes according to edge types. Each class has a different codebook based on its characteristis. Encoder classified each block to motion block or stationary block and constructed a merging map by using edge and motion information, and sent to decoder. We controled amoutn of bing bits transmitted with selecting modes accoridng to bandwidth of transmitting channel. Compared with conventional algorithms, H.263 and H.261 at low bit rate, our proposed algorithm shows better picture quality and good performance.

• Journal of international Conference on Electrical Machines and Systems
• /
• 제2권3호
• /
• pp.288-294
• /
• 2013

This paper introduces a novel method of on-line identifying the stator resistance and leakage inductance of dual three phase induction motor (DTPIM). According to the machine mathematical model, the stator resistance and leakage inductance can be estimated using the voltage and current values in harmonic subspace. Thus a method of voltage vector injection in harmonic subspace (VVIHS) is proposed, which causes currents in harmonic space. Then the errors between command and actual harmonic currents are utilized to regulate the machine parameters, including stator resistance and leakage inductance. The principle is presented and analyzed in detail. Experimental results prove the feasibility and validity of proposed method.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1983년도 하계학술회의강연.논문초록집
• /
• pp.135-138
• /
• 1983

This paper studies a variable structure adaptive model following control system which can control a plant in which the parameters of the controlled plant can not be estimated because they vary with time and in which the controlled plant has noise. The values of the feedback gain matrices for given states are obtained the equivalent control law, and the adaptive controller has been designed using the adaptive mechanism which switches the matrices. The adaptive controller minimizes the state error vector, that is, the difference between the state vector of the model and the state vector of the controlled plant. A controlled plant which has time varying parameters, a controlled plant which has only noise, and a controlled plant which has both have been controlled by the designed adaptive controller. The continuous single input-output system has been analysed by computer. This control system may be used to control practical systems by the addition of a microcomputer.

• 한국전산구조공학회:학술대회논문집
• /
• 한국전산구조공학회 1994년도 가을 학술발표회 논문집
• /
• pp.25-30
• /
• 1994

A vector algorithm for calculating the stiffness matrices of reinforced concrete shell elements is presented. The algorithm is based on establishing vector lengths equal to the number of elements. The computational efficiency of the proposed algorithm is assessed on a Cray Y-MP supercomputer. It is shown that the vector algorithm achieves scalar-to-vector speedup of 1.7 to 7.6 on three inelastic problems.