• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.40-47
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work the authors presented an iterative precision of linear decentralized learning control based on p-integrated teaming method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the loaming control field was learning in robots doing repetitive tasks such as on a]1 assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.336-340
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• 2007

This paper proposes a multicast scheme over IEEE 802.16 networks which support multiple upper layer protocols such as ATM, IPv4 packets, IPv6 packets, IEEE 802.3 over IPv4 and so on. The multicast capabilities over IEEE 802.16 are important both control plane and data plane. The proposed multicast scheme can be divided into two types: direct mapping and indirect mapping. The direct mapping scheme is that layer 3 address is directly mapped into CID information which is used for connection identifier at IEEE 802.16 link layer. The indirect mapping scheme has two steps for mapping between layer 3 address and layer 2 CID. Firstly, a layer 3 address translates to Ethernet MAC address with group MAC address. Secondly, a group MAC address is mapped into CID. The mapping scheme depends on the upper layer protocols.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.724-727
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• 1999

In this paper, the direct and indirect neural adaptive controller are combined based on the Lyapunov synthesis approach. The proposed adaptive controller is constructed from RBF neural network and a set of fuzzy IF-THEN rules. And the weighting parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given trajectory. In this scheme, fuzzy IF-THEN rules are used to decide the combined weighting factor. It is shown that all the signals in the closed-loop system are uniformly bounded under mild assumptions. The effectiveness of the proposed control scheme is demonstrated through the control of one-link rigid robotics manipulator.

• Asian Journal for Public Opinion Research
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• v.11 no.3
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• pp.182-200
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• 2023

A recent nationwide survey reported that South Koreans perceive large corporations as the party that should be the most responsible for tackling climate change. This public opinion result offers insight into the argument that defining who is responsible for the climate change issue can guide campaigners and policymakers in designing effective communication strategies. This study examines how attributing responsibility to large corporations can affect behavioral intention to support government policy and regulation via a moderated mediation model of the perceived risk of climate change and corporate social responsibility (CSR). A nationwide online survey of 295 South Koreans was conducted. The findings reveal an indirect effect of responsibility attribution on behavioral intention through risk perception. Moreover, perceived CSR moderated the causal link between risk perception and behavioral intention, such that South Koreans reported higher levels of behavioral intention when they reported higher CSR. However, perceived CSR failed to moderate the indirect effect. These findings have implications for communication processes and policymaking to address climate change problems in South Korea.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1536-1543
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• 2019

This paper presents an improved torque predictive control (TPC) for permanent magnet synchronous motors (PMSMs) using an indirect matrix converter (IMC). The IMC has characteristics such as a high power density and sinusoidal waveforms of the input-output currents. Additionally, this configuration does not have any DC-link capacitors. Due to these advantages of the IMC, it is used in various application field such as electric vehicles and railway cars. Recently, research on various torque control methods for PMSM drives using an IMC is being actively pursued. In this paper, an improved TPC method for PMSM drives using an IMC is proposed. In the improved TPC method, the magnitudes of the voltage vectors applied to control the torque and flux of the PMSM are adjusted depending on the PMSM torque control such as the steady state and transient response. Therefore, it is able to reduce the ripples of the output current and torque in the low-speed and high-speed load ranges. Additionally, the improved TPC can improve the dynamic torque response when compared with the conventional TPC. The effectiveness of the improved TPC method is verified by experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.720-729
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• 2005

In this paper, we design the indirect adaptive controller using Wavelet Neural Network(WNN) for unknown nonlinear systems. The proposed indirect adaptive controller using WNN consists of identification model and controller. Here, the WNN is used in both Identification model and controller The WNN has advantage of indicating the location in both time and frequency simultaneously, and has faster convergence than MLPN and RBFN. There are several training methods for WNN, such as GD, GA, DNA, etc. In this paper, we present the Extended Kalman Filter(EKF) based training method. Although it is computationally complex, this algorithm updates parameters consistent with previous data and usually converges in a few iterations. Finally, ore illustrate the effectiveness of our method through computer simulations for the Buffing system and the one-link rigid robot manipulator. From the simulation results, we show that the indirect adaptive controller using the EKF method has better performance than the GD method.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.3
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• pp.88-96
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• 1995

High speed elevator requires precise drive included in zero speed at start/stop drive for the high stability and controllability. The vector control techniques, which have been used for the precise operation of induction motor, can be divided into two classes; The indirect vector control by slip frequency and the direct vector control by field orientation. The existing direct vector control technique has a robustness against the change of motor parameter and the existing indirect vector control technique has a strength of control ability in the wide speed range comparatively. This study presents the DTIF (Direct Torque Indirect Flux) controller which has robust movement in the transition state and in about zero and low speed using the control technique in which torque is controlled by the direct vector technique and flux is controled by indirect vector technique. The proposed system is verified by simulation and experiment for driving 3 phase induction motor. The process of transition which is from about zero speed and low speed to high speed is compared and measured to specification of phase voltage, phase current and DC link current. It is verified that DTIF controller show robust and stable speed variation.

• Proceedings of the KIEE Conference
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• 2003.10b
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• pp.141-143
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• 2003

This paper proposes a new sensorless drive system for the trapezoidal Brushless Direct Current (BLDC) motor requiring mechanical position or speed sensor. The proposed method is using only one current sensor For this an indirect rotor position sensing method from the periodically variation DC Link current waveform. DC Link current waveform change from high to low when BLDC commutate status. This algorithm was verified by simulations using MATLAB SIMULINK and experiment.