• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.2
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• pp.15-19
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• 2022

Purpose: This pilot study aimed to clarify features of motor module during walking in exercise experts who experienced lately repeated training for sports skill. To identify motor modules, autoencoder machine learning algorithm was used, and modules were extracted from muscle activities of lower extremities. Research design, data and methodology: A total of 10 university students were participated. 5 students did not experience any sports training before, and 5 students did experience sports training more than 5 years. Eight muscle activities of dominant lower extremity were measured. After modules were extracted by autoencoder, the numbers of modules and spatial muscle weight values were compared between two groups. Results: There was no significant difference in the minimal number of motor modules that explain more than 90% of original data between groups. However, in similarity analysis, three motor modules were shown high similarity (r>0.8) while one module was shown low similarity (r<0.5). Conclusions: This study found not only common motor modules between exercise novice and expert during walking, but also found that a specific motor module, which would be associated with high motor control ability to distinguish the level of motor performance in the field of sports.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.1
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• pp.1-7
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• 2022

Purpose: This study aimed to investigate spatial and temporal features of motor control in an individual with hemiparesis during the curvilinear gait (CG) and proposed an exercise guideline. Research design, data and methodology: An individual aged 63 with hemiparesis by stroke disease was participated in the study. Autoencoder (AE) was used to extract four motor modules from eight muscle activities of the paretic leg during CG. After extraction, each module of four modules was operationally defined by numbering from M1 to M4 according to spatial and temporal features and compared with results reported in a previous study. Results: As a result, an individual with hemiparesis had motor module problems related to difficulty of weight acceptance (module 1), compensation for the weakness of ankle plantar flexor (module 2), a spastic synergistic pattern (module 3) and difficulty with transition from the swing to stance phase (module 4) in terms of spatial features. Also, a delayed activation timing of temporal motor module (module 2) related to the forward propulsion during CG was observed. Conclusions: Gait rehabilitation for the stroke will need to consider clinical significances in respect of the deterioration of motor module and provide the tailored approaches for each gait phase.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.173-184
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• 2018

In human walking, muscle co-contraction which produces simultaneous activities of multiple muscles is important in motor control mechanism of the central nervous system. This study aims to understand positive and negative covariation mechanism of inter-muscle activities during walking. In this study, we measured electromyography (EMG) in leg muscles. To identify motor modules, we recored EMG from 4 leg muscles bilaterally (the tibialis anterior, medial gastrocnemius, rectus femoris and medial hamstring muscles) and performed non-negative matrix factorization (NMF) and principa component analysis (PCA). Then, we computed covariation values from various combinations between muscles or motor modules and used two-way repeated measures analysis of variance to identify significantly different covariation patterns between muscle combinations. As the results, we found significant differences between covariation values of muscle combinations (p < 0.05). muscle groups within the same motor modules produced the positive covariations. However, there were strong negative covariation between motor modules. There was negative covariation in all muscle combination. Stable inter-module negative covariation suggests that motor modules may be the control unit in the complex motor coordination.

• Journal of Power Electronics
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• v.11 no.3
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• pp.279-284
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• 2011

Network-based controls for ac motor drive systems are becoming increasingly important. In this paper, an ac motor control system is implemented by a motor control module and three sensor modules such as a voltage sensor module, a current sensor module, and an encoder module. There will inevitably be network time delays from the sensor modules to the motor control system, which often degrades and even destabilizes the motor drive system. As a result, it becomes very difficult to estimate the network delayed ac sensor data. An algorithm to reduce the effects of network time delays on sensor data is proposed, using both a synchronization signal and a simple method for estimating the sensor data. The algorithm is applied to a vector controlled induction motor drive system, and the performance of the proposed algorithm is verified with experiments.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.379-387
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• 2013

This paper describes a scheme of motor control for Quadcopter with Android phone instead of a dedicated controller. Basically, user's requests (channel and speed) are inquired and transferred to the Quadcopter with Android phone, then the embedded Linux system receives them and controls the motor speed of corresponding channel. We have designed and implemented an App. for user interface and the modules of device driver and timer ISR for the motor control. Finally, we have up-loaded the App. and the modules to an Android (ver.4.0) phone and ARM processor (S3C6410)-based embedded board respectively, and reviewed the functional correctness by testing the motor control of Quadcopter.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.3
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• pp.215-224
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• 2008

In this paper, we introduced a linear motor-based transfer system with an active pid controller which can be replaced with an automated guided vehicle (AGV) for the port automation. This system, which is named LMCTS(liner motor-based container transfer system), is based on PMLSM (permanent magnetic linear synchronous motor) which basically consists of stator modules on the rail and shuttle car. Therefore more progressive and adaptive control mechanisms should be required to control a system with large variation of container weight, the difference of each characteristic of stator modules, a stator module's trouble etc. We introduced an active control mechanism with an online tuning scheme using modified evolutionary strategy. Some computer simulations are implemented to assess the robustness of the proposed system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.6
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• pp.266-271
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• 2001

In this paper, a controller design for coreless linear synchronous motor is proposed. The designed controller is mainly composed of speed and current control, which are carried out by the high-speed digital signal processor(DSP). In addition the PWM inverter is controlled by space voltage PWM method. This system is implemented using by 32-bit DSP(TMS320C31), a high-integrated logic device(EPM940), and IPM(Intelligent Power Modules) for compact and powerful system design. The experimental results show the effective performance of controller for coreless linear synchronous motor.

• Transactions of Materials Processing
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• v.20 no.3
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• pp.206-213
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• 2011

A flexible die, which is composed of a number of punches with adjusted heights to form a three-dimensional curved surface, is a crucial part of a flexible forming technology. In this study, the punch and control system of the flexible die were designed. The flexible die is divided into three modules, namely, punch, control and joint, and the corresponding modules were developed. The punch module materializes a three-dimensional forming surface by the control module, which is composed of an AC servo motor set and a linear guide. The joint module is necessary for the sequential motion between the servo motor set and the punch module. A sequential motion algorithm for the AC servo motor set, that uses the data of the punch relative heights, was also proposed. Finally, a flexible stretch forming test was carried out using the presently designed flexible die.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.392-395
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• 2003

In the maritime container terminal, LMTT (Linear Motor-based Transfer Technology) is horizontal transfer system for the yard automation, which has been proposed to take the place of AGV (Automated Guided Vehicle). The system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car (mover). Because of large variant of mover's weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's trouble etc., LMCPS (Linear Motor Conveyance Positioning System) is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the soft-computing method of a multi-step prediction control for LMCPS using DR-FNN (Dynamically-constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi-step prediction. Consequently, the system has an ability to adapt for external disturbance, cogging force, force ripple, and sudden changes of itself.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.307-310
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• 2003

In the maritime container terminal, LMTT(Linear Motor-based Transfer Technology) is horizontal transfer system for the yard automation, which has been proposed to take the place of AGV(Automated Guided Vehicle). The system is based on PMLSM (Permanent Magnetic Linear Synchronous Motor) that is consists of stator modules on the rail and shuttle car (mover). Because of large variant of mover's weight by loading and unloading containers, the difference of each characteristic of stator modules, and a stator module's trouble etc., LMCPS (Linear Motor Conveyance Positioning System) is considered as that the system is changed its model suddenly and variously. In this paper, we will introduce the soft-computing method of a multi-step prediction control for LMCPS using DR-FNN (Dynamically-constructed Recurrent Fuzzy Neural Network). The proposed control system is used two networks for multi-step prediction. Consequently, the system has an ability to adapt for external disturbance, cogging force, force ripple, and sudden changes of itself.