• Journal of Mechanical Science and Technology
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• v.17 no.10
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• pp.1443-1449
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• 2003

Primary goal of adaptive observers would be to estimate the true states of a plant. Identification of unknown parameters is of secondary interest and is achieved frequently with the persistent excitation condition of some regressors. Nevertheless, two problems are linked to each other in the classical approaches to adaptive observers; as a result, we get a good state estimate once after a good parameter estimate is obtained. This paper focuses on the state estimation without parameter identification so that the state is estimated regardless of persistent excitation. In this direction of research, Besancon (2000) recently summarized that most of adaptive observers in the literature share one common canonical form, in which unknown parameters do not affect the unmeasured states. We enlarge the class of linear systems from the canonical form of (Besancon, 2000) by proposing an adaptive observer (with additional dynamics) that allows unknown parameters to affect those unmeasured states. A recursive algorithm is presented to design the proposed dynamic observer systematically. An example confirms the design procedure with a simulation result.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.61-64
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• 1996

This paper presents a new approach to the design of self-tuning adaptive control system that is robust to the changing dynamic configuration as well as to the load variation factors using Digital signal processors for robot manipulators. TMS32OC50 is used in implementing real-time adaptive control algorithms to provide advanced performance for robot manipulator. In this paper, an adaptive control scheme is proposed in order to design the pole-placement self-tuning controller which can reject the offset due to any load disturbance without a detailed description of robot dynamics. Parameters of discrete-time difference model are estimated by the recursive least-square identification algorithm, and controller parameters are determined by the pole-placement method. Performance of self-tuning adaptive controller is illustrated by the simulation and experiment for a SCARA robot.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.6
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• pp.487-491
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• 2008

Tuning of the speed controller in the linear servo applications needs the accurate information of a mover mass including a load mass. Therefore this paper proposes the mass estimation method of a permanent magnet linear synchronous motor(PMLSM) applied at the vertical axis by using the recursive Least-Squares estimation algorithm. First, this paper derives the deterministic autoregressive moving average(DARMA) model of the mechanical dynamic system used at the vertical axis. The application of the Least-Squares algorithm to the derived DARMA model gives the mass estimation method. Matlab/Simulink-based simulation and experimental results show that the total mover mass of a PMLSM applied at the vertical axis can be accurately estimated at both no-load and load conditions.

• Journal of Power Electronics
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• v.9 no.4
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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.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2949-2952
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• 2000

A new neural networks and learning algorithm are proposed in order to measure nonlinear heights of complexed road environments in realtime without pre-information. This new neural networks is Error Self Recurrent Neural Networks(ESRN), The structure of it is similar to recurrent neural networks: a delayed output as the input and a delayed error between the output of plant and neural networks as a bias input. In addition, we compute the desired value of hidden layer by an optimal method instead of transfering desired values by back-propagation and each weights are updated by RLS(Recursive Least Square). Consequently. this neural networks are not sensitive to initial weights and a learning rate, and have a faster convergence rate than conventional neural networks. We can estimate nonlinear models in realtime by ESRN and learning algorithm and control nonlinear models. To show the performance of this one. we control 7 degree of freedom full car model with several control method. From this simulation. this estimation and controller were proved to be effective to the measurements of nonlinear road environment systems.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.543-549
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• 2021

In this paper, a robust transfer alignment method is proposed for a strapdown inertial navigation system(SDINS) with norm-bounded parametric uncertainties. The uncertainties are described by the energy bound constraint, i.e., sum quadratic constraint(SQC). It is shown that the SQC can be coverted into an indefinite quadratic cost function in the Krein space. Krein space Kalman filter is designed by modifying the measurement matrix and the variance of measurement noises in the conventional Kalman filter. Since the proposed Krein space Kalman filter has the same recursive structure as a conventional Kalman filter, the proposed filter can easily be designed. The simulation results show that the proposed filter achieves robustness against measurement time delay and high dynamic environment of the vehicle.

• Journal of KSNVE
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• v.9 no.6
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• pp.1259-1266
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• 1999

The objective of this investigation is to develop a compliant track link model and apply this model to the multi-body dynamic analysis of high mobility tracked vehicles. Two major difficulties encountered in developing the compliant track models. The first one is that the integration step size must be kept small in order to maintain the numerical stability of the solution. This solution deals with high oscillatory signals resulting from the impulsive contact forces and stiff compliant elements to represent the joints between the track links. The second difficulty is due to the large number of the system equations of motion of the three dimensional multibody tracked vehicle model. This problem was sloved by decoupling the equations of motion of the chassis subsystem and the track subsystems. Recursive methods are used to obtain a minimum set of equations for the chassis subsystem. Several simulation scenarios were tested for the high mobility tracked vehicle including accelaeration, high speed cruising, braking, and turning motion in order to demonstrate the effectiveness and validity of the methods proposed in this investigation.

• Korean Journal of Agricultural Science
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• v.50 no.4
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• pp.629-643
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• 2023

The purpose of this study was to examine the effectiveness and efficiency of a policy by comparing and analyzing the impact of the rice market isolation system and production adjustment system (strategic crops direct payment system that induces the cultivation of other crops instead of rice) on rice supply, rice price, and government's financial expenditure. To achieve this purpose, a rice supply and demand forecasting and policy simulation model was developed in this study using a partial equilibrium model limited to a single item (rice), a dynamic equation model system, and a structural equation system that reflects the casual relationship between variables with economic theory. The rice policy analysis model used a recursive model and not a simultaneous equation model. The policy is distinct from that of previous studies, in which changes in government's policy affected the price of rice during harvest and the lean season before the next harvest, and price changes affected the supply and demand of rice according to the modeling, that is, a more specific policy effect analysis. The analysis showed that the market isolation system increased government's financial expenditure compared to the production adjustment system, suggesting low policy financial efficiency, low policy effectiveness on target, and increased harvest price. In particular, the market isolation system temporarily increased the price during harvest season but decreased the price during the lean season due to an increase in ending stock caused by increased production and government stock. Therefore, a decrease in price during the lean season may decrease annual farm-gate prices, and the reverse seasonal amplitude is expected to intensify.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.303-311
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• 2020

The acreage of tangerines in the U.S. sharply rose from 19,000 ha in 2009 to 27,000 ha in 2016, an increase of 42% in 7 years. Considering the recent surge in tangerine exports to Japan, the export volume of 6-7 thousand tons is highly likely to increase in the future. Therefore, the purpose of this study was to analyze the economic impact of U.S. tangerine imports on the Korean citrus industry under various scenarios. In order to examine the possibility of imports of U.S. tangerines, the unit price of U.S. exports to Japan was used since U.S. tangerines are not imported to South Korea. Citrus fruits are divided into field citrus, house citrus, and late-maturing citrus (including winter season citrus) based on the cultivation method and variety used to analyze. Considering both the field and house seasons, the import volume of U.S. tangerines can be expected to rise from roughly 4,700 tons in 2021 to 10,000 tons in 2027. Imports of U.S. tangerines may be pushed up or delayed depending not only on the harvest method and quality of domestic field and house citrus but also on the harvest of U.S. tangerines. However, it is necessary to note that tangerines could be imported after 2021, when the tariff rate on U.S. tangerines will fall below 50%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.108-114
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• 2021

Green colored citrus is the immature fruit of the field citrus crop in Jeju, and its demand has been growing recently as it is known to contain a large amount of carotinoid, pectin, and vitamin C. It differs from the traditional varieties of blue tangerine, which are green in February and turn in yellow in March-April. This study analyzed the effects of the increased demand in green citrus on the field citrus industry. For our analysis, a partial equilibrium supply-demand model was established with a dynamic recursive structure using data from 1989-2017. Model calibration was also conducted to determine the best supply-demand model and then, the impacts of increasing demand for green immature citrus in Jeju for 2018-2030 was simulated. The simulation results show that there is no significant impact on the producing area prior to 2022, but there is a distinguishable increase of 18ha in 2023, 52ha in 2025, and 142ha in 2030. It was also predicted that revenue would increase by KRW 7.75 billion on average from 2021-2030.