• Journal of Power Electronics
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• v.14 no.5
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• pp.980-988
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• 2014

This paper proposes an online gain tuning algorithm for a robust sliding mode speed controller of surface-mounted permanent magnet synchronous motor (SPMSM) drives. The proposed controller is constructed by a fuzzy neural network control (FNNC) term and a sliding mode control (SMC) term. Based on a fuzzy neural network, the first term is designed to approximate the nonlinear factors while the second term is used to stabilize the system dynamics by employing an online tuning rule. Therefore, unlike conventional speed controllers, the proposed control scheme does not require any knowledge of the system parameters. As a result, it is very robust to system parameter variations. The stability evaluation of the proposed control system is fully described based on the Lyapunov theory and related lemmas. For comparison purposes, a conventional sliding mode control (SMC) scheme is also tested under the same conditions as the proposed control method. It can be seen from the experimental results that the proposed SMC scheme exhibits better control performance (i.e., faster and more robust dynamic behavior, and a smaller steady-state error) than the conventional SMC method.

• Journal of Microbiology and Biotechnology
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• v.12 no.3
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• pp.377-381
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• 2002

Recently, interests to remove nitrogen in the nitritation process have increased because of its economical advantages, since it could be a short-cut process to save both oxygen for nitrification and carbon for denitrification compared to a typical nitrification. However, the kinetics related with the nitritation process has not yet been fully understood. Furthermore, many useful models which have been successfully used for wastewater treatment processes cannot be used to estimate effluent nitrite concentration for evaluating performance of the nitritation process, since the process rate equations and population of microorganisms for nitrogen removal in these models have been set up only for the condition of full nitrification. Therefore, the present study was conducted to estimate an effluent nitrite concentration in the nitritation process with a concept of enzymatic inhibition kinetics based on long-term laboratory experiments. Using a nonlinear least squares regression method, kinetic parameters were accurately determined. By setting up a process rate equation along with a mass balance equation of the nitrite-oxidizing step, an effluent nitrite concentration in the nitritation process was then successfully estimated.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.6
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• pp.1445-1451
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• 1994

To calculate the wave pressure acting on coastal structures under the design wave condition, it is often necessary to numerically reproduce the big standing wave profiles close to wave breaking condition. For this, the governing equation and all nonlinear terms occurring in boundary conditions should be effectively considered in the numerical wave profile. In particular, the velocity square term in the free surface boundary condition is very important. A boundary element method is applied here to calculate the standing wave profile with the velocity square term fully treated by Newton iterative method. In order to check the validity of the method, the numerical wave profiles are compared to ones calculated by the perturbation method, the Fourier approximation method and the hydraulic experiment.

• Journal of Power Electronics
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• v.14 no.4
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• pp.704-711
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• 2014

This paper proposes a combined fuzzy adaptive sliding-mode voltage controller (FASVC) for a three-phase UPS inverter. The proposed FASVC encapsulates two control terms: a fuzzy adaptive compensation control term, which solves the problem of parameter uncertainties, and a sliding-mode feedback control term, which stabilizes the error dynamics of the system. To extract precise load current information, the proposed method uses a conventional load current observer instead of current sensors. In addition, the stability of the proposed control scheme is fully guaranteed by using the Lyapunov stability theory. It is shown that the proposed FASVC can attain excellent voltage regulation features such as a fast dynamic response, low total harmonic distortion (THD), and a small steady-state error under sudden load disturbances, nonlinear loads, and unbalanced loads in the existence of the parameter uncertainties. Finally, experimental results are obtained from a prototype 1 kVA three-phase UPS inverter system via a TMS320F28335 DSP. A comparison of these results with those obtained from a conventional sliding-mode controller (SMC) confirms the superior transient and steady-state performances of the proposed control technique.

• Selected Papers of The Society of Naval Architects of Korea
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• v.2 no.1
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• pp.63-78
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• 1994

This paper deals with the treatment of the open boundary in two-dimensional free-surface wave problems. Two numerical schemes are investigated for the implementation of the open boundary condition. One is to add the artificial damping term to the dynamic free-surface boundary condition, in which the determination of suitable damping coefficient and the damping zone is the most important. The other is a modified Orlanski's method, which is known to be very useful for the uni-directional waves. Using these two schemes, numerical tests have been conducted for a few typical free-surface wave problems. To obtain the numerical solution of the free-surface boundary value problem, the fundamental source-distribution method is used and the fully nonlinear free-surface boundary conditions are applied. The computed results are presented in comparison with those of others for the proof of practicality of these two schemes.

• Journal of Ocean Engineering and Technology
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• v.19 no.3
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• pp.18-24
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• 2005

Wave overtopping is one of the most important processes for the design of seawalls. The term "wave overtopping" is used here to refer to the processes where waves hit a sloping structure run up the slope and, if the crest level of the slope is lower than the highest run up level, overtop the structure. Wave overtopping is dependent on the processes associated with breaking wave. A numerical model based on Navier-Stokes equation and the Marker-density function for predicting wave overtopping of coastal structures is developed in this paper. In order to evaluate the present model, two simulations are tested. One is overflow without waves at vertical seawall, and the other is wave overtopping at sloping seawalls.

• Journal of the Society of Naval Architects of Korea
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• v.29 no.3
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• pp.80-89
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• 1992

This paper deals with the open boundary problems, and two numerical schemes are used for the implementation of open boundary condition. One is to add the artificial damping term to dynamic free-surface boundary condition. Determination of suitable damping coefficient and the damping cone is the most important in this scheme. The other scheme is a modified Orlanski's method. This will be useful for the problems with unidirectional waves. A few typical free-surface wave problems are modeled for the numerical test. Method of solution is fundamental source-distribution method and the fully nonlinear boundary conditions are applied. The computed results are compared with those of others for the proof of practicality of these schemes.

• Smart Structures and Systems
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• v.24 no.6
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• pp.733-744
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• 2019

Wind speed forecasting is critical for a variety of engineering tasks, such as wind energy harvesting, scheduling of a wind power system, and dynamic control of structures (e.g., wind turbine, bridge, and building). Wind speed, which has characteristics of random, nonlinear and uncertainty, is difficult to forecast. Nowadays, machine learning approaches (generalized regression neural network (GRNN), back propagation neural network (BPNN), and extreme learning machine (ELM)) are widely used for wind speed forecasting. In this study, two schemes are proposed to improve the forecasting performance of machine learning approaches. One is that optimization algorithms, i.e., cross validation (CV), genetic algorithm (GA), and particle swarm optimization (PSO), are used to automatically find the optimal model parameters. The other is that the combination of different machine learning methods is proposed by finite mixture (FM) method. Specifically, CV-GRNN, GA-BPNN, PSO-ELM belong to optimization algorithm-assisted machine learning approaches, and FM is a hybrid machine learning approach consisting of GRNN, BPNN, and ELM. The effectiveness of these machine learning methods in wind speed forecasting are fully investigated by one-year field monitoring data, and their performance is comprehensively compared.

• Journal of the Korea Institute of Building Construction
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• v.14 no.6
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• pp.631-637
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• 2014

Recently, following the application of modular housing techniques to not only residential sector, but also to business sector, the scope of modular housing market b expanding. In the case of other developed countries, such markets are entering into the maturity stage, though the market in Korea is not fully formed yet. Thus, it is difficult to check its trend to estimated mid- to long-term prospects of the market. In this context, the study predicted demand of the modular housing market by using a non-linear prediction model based on time series analysis. To get the prospects for the modular housing market, the quantity of housing supply was estimated based on the estimated quantity of newly built housings, and assumed that a portion of the supplied quantity would be the demand for modular housings. Based on the assumption of demand for modular housings, several scenarios were analyzed and the prospects of the modular housing market was obtained by utilizing the non-linear prediction model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.6B
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• pp.543-550
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• 2009

The traditional simple extrapolation type short term quantitative rainfall forecast can not realize the evolution of rainfall generating weather system. To overcome the drawback of the linear extrapolation type rainfall forecasting model, the history of a weather system from sequential weather radar information and a polynomial regression technique were used to generate forecast fileds of x-directional, y-directional velocities and radar reflectivity which considered the nonlinear behavior related to the evolution of weather systems. Results demonstrated that test statistics of forecasts using the developed model is better than that of 2-CAPPI forecast. However there is still a large room to improve the forecast of spatial and temporal evolution of local storms since the model is not based on a fully physical approach but a statistical approach.