• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.378-387
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• 2007

In this paper, Authors develop and verify the algorithm for enhancing the performance of Unmanned vehicle's Autonomous navigation, and also propose the method of establishing much more precise Navigation locus. Unmanned vehicle has a destination, however orientation is not notified, which make it find the future orientation itself. Extended Kalman Filter make it access to the desirable direction, which coupled with INS and GPS is proposed in this paper. Sliding mode control could overcome the side slip and lateral minor movement of the vehicle. The test result would shows the effectiveness of Extended kalman filter and Slide mode control for the navigation.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1275-1278
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• 1997

Cutting process has been automated by progress of CNC and CAD/CAM, but polishing process has been depended on only experiential knowledge of expert. To automate the polishing pricess polishing robot with 2 degrees of freedom which is attached to a machining center with 3 degrees of freedom has been developed. this automatic polishing robot is able to keep the polishing tool normal on the curved surface of die to improve a performance of polishing. Polishing task for a curved surface die demands repetitive operation and high precision, but conventional control algorithm can not cope with the problem of disturbance such as a change of load. In this research, we develop robust controller using real time sliding mode algorithm. To obtain gain parameters of sliding model control input, the signal compression method is used to identify polishing robot system. To obtain an effect of 5 degrees of freedom motion, 5 axes NC data for polishing are divided into data of two types for 3 axis machining center and 2 axis polishing are divided into data of two types for 3 axis machining center and 2 axis polishing robot. To find an efficient polishing condition to obtain high quality, various experiments are carried out.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.2
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• pp.278-294
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• 2015

Considering the guidance and control problem of the near space interceptor (NSI) during the terminal course, this paper proposes a three-channel independent integrated guidance and control (IGC) scheme based on the backstepping sliding mode and finite time disturbance observer (FTDO). Initially, the three-channel independent IGC model is constructed based on the interceptor-target relative motion and nonlinear dynamic model of the interceptor, in which the channel coupling term and external disturbance are regarded as the total disturbances of the corresponding channel. Then, the FTDO is introduced to estimate the target acceleration and control system loop disturbances, and the feed-forward compensation term based on the estimated values is employed to effectively remove the effect of disturbances in finite time. Subsequently, the IGC algorithm based on the backstepping sliding mode is also given to obtain the virtual control moment. Furthermore, a robust least-squares weighted control allocation (RLSWCA) algorithm is employed to distribute the previous virtual control moment among the corresponding aerodynamic fins and reaction jets, which also takes into account the uncertainty in the control effectiveness matrix. Finally, simulation results show that the proposed IGC method can obtain the small miss distance and smooth interceptor trajectories.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.6
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• pp.194-207
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• 2000

In this paper, we suggest a vision-based lane change control system, which can be applied on the straight road, without additional sensors such as a yaw rate sensor and a lateral accelerometer. In order to reduce the image processing time, we predict a reference line position during lane change using the lateral dynamics and the inverse perspective mapping. The sliding mode control algorithm with a boundary layer is adopted to overcome variations of parameters that significantly affects a vehicle`s lateral dynamics and to reduce chattering phenomenon. However, applying the sliding mode control to the system with a long sampling interval, the stability of a control system may seriously be affected by the sampling interval. Therefore, in this paper, a look ahead offset has been used instead of a lateral offset to reduce the effect of the long sampling interval due to the image processing time. The control algorithm is developed to follow the desired trajectory designed in advance. In the design of the desired trajectory, we take account of the constraints of lateral acceleration and lateral jerk for ride comfort. The performance of the suggested control system is evaluated in simulations as well as field tests.

• Smart Structures and Systems
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• v.11 no.3
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• pp.315-329
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• 2013

The construction of an experimental nonlinear structural model with little cost and unlimited repeatability for vibration control study represents a challenging task, especially for material nonlinearity. This paper reports the design, analysis and vibration control of a nonlinear structural experiment platform with adjustable hinges. In our approach, magnetorheological rotary brakes are substituted for the joints of a frame structure to simulate the nonlinear material behaviors of plastic hinges. For vibration control, a separate magnetorheological damper was employed to provide semi-active damping force to the nonlinear structure. A dynamic neural network was designed as a state observer to enable the feedback based semi-active vibration control. Based on the dynamic neural network observer, an adaptive fuzzy sliding mode based output control was developed for the magnetorheological damper to suppress the vibrations of the structure. The performance of the intelligent control algorithm was studied by subjecting the structure to shake table experiments. Experimental results show that the magnetorheological rotary brake can simulate the nonlinearity of the structural model with good repeatability. Moreover, different nonlinear behaviors can be achieved by controlling the input voltage of magnetorheological rotary damper. Different levels of nonlinearity in the vibration response of the structure can be achieved with the above adaptive fuzzy sliding mode control algorithm using a dynamic neural network observer.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.6
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• pp.28-36
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• 2001

A robust adaptive sliding mode robot control algorithm is derived, which consists of a feed-forward compensation part and discontinuous control part. The unknown parameters is categorized into two groups, with group containing the parameters estimated on-line, and group containing the parameters not estimated on-line. Then a sliding control term is incorporated into the torque input in order to account for the effects of uncertainties on the parameters not estimated on-line and of disturbances. Moreover, the algorithm is computationally simple, due to an effective exploitation of the structure of manipulator dynamics. It is shown that, despite the existence of the parameter uncertainty and external disturbances, the controller is globally asymptotically stable and guarantees zero tracking errors.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.2
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• pp.103-110
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• 2011

It is necessary to accurate and efficient management for measured digital data from sensors in u-health system. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using backpropagation algorithm. As a result, we obtained to efficient result about 18.3% reduction rate of database using 14,324 data sets.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1012-1024
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• 2016

This study deals with an on-line software fault detection, localization, and system reconfiguration method for electrical system drives composed of three-phase AC/DC/AC converters and three-phase permanent magnet synchronous machine (PMSM) drives. Current sensor failure (outage), speed/position sensor loss (disconnection), and damaged DC-link voltage sensor are considered faults. The occurrence of these faults in PMSM drive systems degrades system performance and affects the safety, maintenance, and service continuity of the electrical system drives. The proposed method is based on the monitoring signals of "abc" currents, DC-link voltage, and rotor speed/position using a measurement chain. The listed signals are analyzed and evaluated with the generated residuals and threshold values obtained from a Sliding Mode Current-Speed-DC-link Voltage Observer (SMCSVO) to acquire an on-line fault decision. The novelty of the method is the faults diagnosis algorithm that combines the use of SMCSVO and adaptive thresholds; thus, the number of false alarms is reduced, and the reliability and robustness of the fault detection system are guaranteed. Furthermore, the proposed algorithm's performance is experimentally analyzed and tested in real time using a dSPACE DS 1104 digital signal processor board.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.330-341
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• 2007

This work analyzes the performance of the parallel packet switch (PPS) with a sliding window (SW) method. The PPS involves numerous packet switches that operate independently and in parallel. The conventional PPS dispatch algorithm adopts a round robin (RR) method. The class of PPS is characterized by deployment of parallel low-speed switches whose all memory buffers run more slowly than the external line rate. In this work, a novel SW packet switching method for PPS, called SW-PPS, is proposed. The SW-PPS employs memory space more effectively than the existing PPS using RR algorithm. Under identical Bernoulli and bursty data traffic, the SW-PPS provided significantly improved performance when compared to PPS with RR method. Moreover, this investigation presents a novel mathematical analytical model to evaluate the performance of the PPS using RR and SW method. Under various operating conditions, our proposed model and analysis successfully exhibit these performance characteristics including throughput, cell delay, and cell drop rate.

• Journal of Drive and Control
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• v.19 no.1
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• pp.51-61
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• 2022

This paper presents a model-free system based on a framework of a backstepping sliding mode control (BSMC) with a radial basis function neural network (RBFNN) and adaptive mechanism for electro-hydraulic systems (EHSs). First, an EHS mathematical model was dedicatedly derived to understand the system behavior. Based on the system structure, BSMC was employed to satisfy the output performance. Due to the highly nonlinear characteristics and the presence of parametric uncertainties, a model-free approximator based on an RBFNN was developed to compensate for the EHS dynamics, thus addressing the difficulty in the requirement of system information. Adaptive laws based on the actor-critic neural network (ACNN) were implemented to suppress the existing error in the approximation and satisfy system qualification. The stability of the closed-loop system was theoretically proven by the Lyapunov function. To evaluate the effectiveness of the proposed algorithm, proportional-integrated-derivative (PID) and improved PID with ACNN (ACPID), which are considered two complete model-free methods, and adaptive backstepping sliding mode control, considered an ideal model-based method with the same adaptive laws, were used as two benchmark control strategies in a comparative simulation. The simulated results validated the superiority of the proposed algorithm in achieving nearly the same performance as the ideal adaptive BSMC.