• The Journal of Engineering Geology
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• v.28 no.3
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• pp.367-377
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• 2018

This study introduces a DC resistivity inversion method that incorporates structural and inequality constraints to enhance the resolution of resistivity inversions, and presents sample inversion results with these constraints. In the constrained inversions, a base model is constructed from a layered model through interpretation of other geophysical data. Inversion tests establish that both the structural and inequality constraints produce better resistivity models than the unconstrained inversion. However, the inequality inversion not only reproduces the exact layered structure of the background, it reproduces conductive anomalies at a depth of ~ 10 m when an inexact base model of electrical resistivity is used.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.75-82
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• 2006

In this paper, we propose an optimal trajectory for biped robots to move up-and-down stairs using a genetic algorithm and a computed-torque control for biped robots to be dynamically stable. First, a Real-Coded Genetic Algorithm (RCGA) which of operators are composed of reproduction, crossover and mutation is used to minimize the total energy. Constraints are divided into equalities and inequalities: Equality constraints consist of a position condition at the start and end of a step period and repeatability conditions related to each joint angle and angular velocity. Inequality constraints include collision avoidance conditions of a swing leg at the face and edge of a stair, knee joint conditions with respect to the avoidance of the kinematic singularity, and the zero moment point condition with respect to the stability into the going direction. In order to approximate a gait, each joint angle trajectory is defined as a 4-th order polynomial of which coefficients are chromosomes. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot that consists of seven links in the sagittal plane. The trajectory is more efficient than that generated by the modified GCIPM. And various trajectories generated by the proposed GA method are analyzed in a viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.119-122
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• 2003

The aim of this paper is to propose a nonlinear controller for a single cart-type inverted pendulum using energy-based control scheme. Using a nonlinear model relating the angular position and velocity to the control input and a nonlinear controller is designed to regulate the angular position and velocity in the presence of input constraints. It is proved that the angular position and velocity converge to zero.

• Korean Journal of Computational Design and Engineering
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• v.18 no.2
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• pp.120-128
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• 2013

Recently, the importance of the HVAC system (Heating, Ventilating and Air Conditioning System) is growing because comfortable working environment has emerged as important element for enhancing work efficiency. HVAC system is a general term of a system that collectively creates desired temperature and state through heating and air conditioning. HVAC system consists of many objects, so it requires a lot of constraints for its effective operation. Thus, specific strategy is needed for an optimal operation of HVAC System for plant. In this paper, manufacturing plants which have HVAC systems has been modeled and the objective function and constraints for an effective operation have been defined. And new strategy for an effective operation of HVAC system with energy simulations has been proposed.

• Journal of information and communication convergence engineering
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• v.15 no.2
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• pp.79-84
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• 2017

In a cognitive radio network (CRN), cognitive radio users (CUs) should be powered by a small battery for their operations. The operations of the CU often include spectrum sensing and data transmission. The spectrum sensing process may help the CU avoid a collision with the primary user (PU) and may save the energy that is wasted in transmitting data when the PU is present. However, in a time-slotted manner, the sensing process consumes energy and reduces the time for transmitting data, which degrades the achieved throughput of the CRN. Subsequently, the sensing process does not always offer an advantage in regards to throughput to the CRN. In this paper, we propose a scheme to find an optimal policy (i.e., perform spectrum sensing before transmitting data or transmit data without the sensing process) for maximizing the achieved throughput of the CRN. In the proposed scheme, the data collection period is considered as the main factor effecting on the optimal policy. Simulation results show the advantages of the optimal policy.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.28-37
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• 2008

In this paper, we investigate the problem of minimizing the average transmission power of users while guaranteeing the average delay constraints in time-varying uplink channels. We design a scheduler that selects a user for transmission and determines the transmission rate of the selected user based on the channel and backlog information of users. Since it requires prohibitively high computation complexity to determine an optimal scheduler for multi-user systems, we propose a low-complexity scheduling scheme that can achieve near-optimal performance. In this scheme, we reduce the complexity by decomposing the multiuser problem into multiple individual user problems. We arrange the probability of selecting each user such that it can be determined only by the information of the corresponding user and then optimize the transmission rate of each user independently. We solve the user problem by using a dynamic programming approach and analyze the upper and lower bounds of average transmission power and average delay, respectively. In addition, we investigate the effects of the user selection algorithm on the performance for different channel models. We show that a channel-adaptive user selection algorithm can improve the energy efficiency under uncorrelated channels but the gain is obtainable only for loose delay requirements in the case of correlated channels. Based on this, we propose a user selection algorithm that adapts itself to both the channel condition and the backlog level, which turns out to be energy-efficient over wide range of delay requirement regardless of the channel model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1467-1472
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• 2011

This paper presents an optimal operation of microgrid systems and considering a tie-lines capacities that concerned each grid. The microgrid system consists of a wind turbine, a diesel generator, and a fuel cell. An one day load profile and wind resource for wind turbine generator were used for the study. For the grid interconnection, tie-line capacities were applied as constraints. The capacity constraints of tie-lines in production cost analysis are very important issues in the operation and planning of microgrid. In optimization, the Harmony Search (HS) algorithm is used for solving the problem of microgrid system operation which a various generation resources are available to meet the customer load demand with minimum operating cost. The application of HS algorithm to optimal operation of microgrid proves its effectiveness to determine optimally the generating resources without any differences of load mismatch.

• Journal of Power Electronics
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• v.9 no.6
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• pp.919-928
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• 2009

Microgrids (MGs) are typically comprised of distributed generators (DGs) including renewable energy sources (RESs), storage devices and controllable loads, which can operate in either interconnected or isolated mode from the main distribution grid. This paper introduces a novel dynamic programming (DP) approach to MG optimization which takes into consideration the coordination of energy supply in terms of heat and electricity. The DP method has been applied successfully to several cases in power system operations. In this paper, a special emphasis is placed on the uncontrollability of RESs, the constraints of DGs, and the application of demand response (DR) programs such as directed load control (DLC), interruptible/curtaillable (I/C) service, and/or demand-side bidding (DSB) in the deregulated market. Finally, in order to illustrate the optimization results, this approach is applied to a couple of examples of MGs in a certain configuration. The results also show the maximum profit that can be achieved.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.575-577
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• 2003

With the deregulation of the power industries in many countries, the trend is towards accommodating more freedom and choice to the market participants and encouraging competition as much as possible in the power market. In this regards, the necessity of market simulation is increasing in order to guarantee a secure and reliable operation of an electricity market. This paper presents the technique of market simulation considering constraints such as energy resource and transmission interface using commercial market simulator.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.315-319
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• 2015

We consider a late decaying dark matter model in which cold dark matter begins to decay into relativistic particles at a recent epoch ($z{\leqslant}1$). A complete set of Boltzmann equations for dark matter and other relevant particles particles is derived, which is necessary to calculate the evolution of the energy density and density perturbations. We show that the large entropy production and associated bulk viscosity from such decays leads to a recently accelerating cosmology consistent with observations. We determine the constraints on the decaying dark matter model with bulk viscosity by using a MCMC method combined with observational data of the CMB and type Ia supernovae.