• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2469-2490
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• 2019

A low-energy adaptive clustering hierarchy (LEACH) protocol is a low-power adaptive cluster routing protocol which was proposed by MIT's Chandrakasan for sensor networks. In the LEACH protocol, the selection mode of cluster-head nodes is a random selection of cycles, which may result in uneven distribution of nodal energy and reduce the lifetime of the entire network. Hence, we propose a new selection method to enhance the lifetime of network, in this selection function, the energy consumed between nodes in the clusters and the power consumed by the transfer between the cluster head and the base station are considered at the same time. Meanwhile, the improved FTBA algorithm integrating the curve strategy is proposed to enhance local and global search capabilities. Then we combine the improved BA with LEACH, and use the intelligent algorithm to select the cluster head. Experiment results show that the improved BA has stronger optimization ability than other optimization algorithms, which the method we proposed (FTBA-TC-LEACH) is superior than the LEACH and LEACH with standard BA (SBA-LEACH). The FTBA-TC-LEACH can obviously reduce network energy consumption and enhance the lifetime of wireless sensor networks (WSNs).

• Journal of Power Electronics
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• v.19 no.3
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• pp.691-701
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• 2019

To solve the problems in the contact charging of inspection robots, a wireless charging system for inspection robots and a control strategy are introduced in this paper. Circuit models of a wireless power system with a compound compensation circuit and a three-phase Class-D resonant inverter are set up based on circuit theory. An output voltage control method based on the equal spread regulation of the phase difference between adjacent phases and the parameter correction method in the primary compound compensation circuit are proposed. The dynamic characteristics of the key parameters varying with the secondary coil position are obtained to further investigate the adaptive location scheme during the access and exit processes of moving robots. Combining the output voltage control method and the adaptive location scheme, a transition control strategy for the standby and operation modes of the wireless charging systems for inspection robots is put forward to realize the system characteristics including the low standby power in the standby mode and the high receiving power in the operation mode. Finally, experiments are designed and conducted to verify the correctness of the theoretical research.

• ETRI Journal
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• v.28 no.6
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• pp.697-708
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• 2006

Various adaptive mesh refinement techniques are often employed in numerical simulations for increasing spatial and temporal resolution beyond the limits imposed by available CPU time and memory space. Recently, an octree-based adaptive mesh structure was successfully used in fluid animation to place more grid cells efficiently in visually interesting regions of fluids. In an attempt to optimize the use of computational resources further in fluid animation, this paper extends this adaptive technique by modifying the mesh refinement scheme so that the camera's viewing properties are dynamically exploited during the simulation. Based on a simple adaptive mesh structure, we show that the new meshing strategy can save a substantial amount of computation time and memory space by using a view-dependent adaptive approach. The experimental results reveal that the proposed technique provides a good compromise between the computational effort and the simulation's fidelity, and may be used quite effectively in 3D animation production.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.61-70
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• 2000

An Adaptive Positive Position Feedback method is presented for controlling the roll of the supersonic smart projectile. The proposed strategy combines the attractive attributes of Positive Position Feedback(PPF) of Goh and Caughey, and Lyapunov stability theorem. The parameters of Adaptive-PFF controller are adjusted in an adaptive mauler in order to follow the performance of an optimal reference model. In this way, optimal damping and zero steady-state errors can be achieved even in the presence of uncertain or changing plant parameters. The performance obtained with the Adaptive-PPF algorithm is compared with conventional PPF control algorithm. The results obtained emphasize the potential of Adaptive-PPF algorithm as an efficient means for controlling plants such as supersonic flight systems with uncertainties in real time.

• Journal of the Korea Society of Computer and Information
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• v.6 no.2
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• pp.48-57
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• 2001

In a fuzzy connectionist expert system(FCES), the knowledge base can be constructed of neural logic networks to represent fuzzy rules and their relationship, We call it fuzzy rule inference network. To find out the belief value of a conclusion, the traditional inference strategy in a FCES will back-propagate from a rule term of the conclusion and follow through the entire network sequentially This sequential search strategy is very inefficient. In this paper, to improve the above search strategy, we proposed fuzzy rule inference rule used in a FCES was modified. The proposed adaptive search strategy in fuzzy rule inference network searches the network according to the search priorities.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.1018-1023
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• 1998

This paper presents an effective control scheme incorporated in the voltage-fed half-bridge series resonant inverter for induction heating applications, which is based upon a load-adaptive tuned frequency tracking control strategy using PLL(Phase Locked Loop) and its peripheral control circuit. The proposed control strategy ensures a stable operation characteristics of overall inverter system and ZVS(Zero Voltage Switching0 operation in spite of sensitive load parameters variation as well as power regulation, specially in the non-magnetic heating loads. The simulation results and the performance characteristics in the steady-state are shown as compared with the experimental results for a prototype induction cooking system rated at 1.2kW.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.6
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• pp.24-29
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• 2001

Adaptive valve timing control is one of the promising techniques to accomplish the optimized mixture formation and combustion depending on the load and speed, which is needed to meet the future challenges in reducing fuel consumption and exhaust emissions. The behavior and the effect of adaptive valve timing control system has been investigated by computer simulation, which simulates the gas dynamics in engines. Improved fuel economy can be achieved by reduction of pumping loss under low and mid load conditions. EIVC(Early Intake Valve Closing) strategy turns out to be superior to LIVC(Late Intake Valve Closing) strategy in reducing fuel consumption. Deterioration of combustion quality can be overcome by introducing LIVO(Late Intake Valve Opening) strategy, which increases turbulent intensity in cylinders. Furthermore, LIVO can reduce HC emission by decreasing the required amount of fuel to be injected during cold start.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.191-197
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• 2004

This paper presents experimental results for human drivers' driving patterns and an Adaptive Cruise Control(ACC) strategy. Analyses have shown that female drivers' driving characteristic values such as time-gap and minimum clearance are larger than those of male drivers'. Human drivers tend to have more clearance margins at high speed than at low speed. At low speed, drivers are much more sensitive to the desired clearance than at high speed. A multi-vehicle detection method is presented to improve ride quality of an ACC. Simulation results have shown that the proposed ACC can provide superior performance compared to the ACC strategy which uses a single-vehicle detection method.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.2
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• pp.19-27
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• 2001

This research attempts to find an active control strategy which reduces acoustic power and acoustic energy in lightly-damped enclosed sound field such as a vehicle compartment or an operating room of heavy industrial machinery. An active control strategy, which takes into consideration of the acoustic radiation power of the source as a cost function, is formulated and examined to find capability of reducing noise. An adaptive filtering algorithm for sound power control is suggested and implemented to control lightly-damped sound field. To verify the method, sound power based active noise control algorithm was implemented on a rectangular box with lightly-damped wall, and popular acoustic energy based control with modal coupling reduction was performed to compare the noise reduction performance. It was shown that a total sound power based strategy provides a practical mean for global noise reduction for lightly damped sound field.

• Proceedings of the KSME Conference
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• 2001.06b
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• pp.724-729
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• 2001

This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.