• Title/Summary/Keyword: load uncertainty

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Adaptive Backstepping Control of Induction Motors Using Neural Network (신경회로망을 이용한 유도전동기의 적응 백스테핑 제어)

  • Lee, Eun-Wook;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.452-455
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    • 2003
  • Based on a field-oriented model of induction motor, adaptive backstepping approach using neural network(RBFN) is proposed for the control of induction motor in this paper. In order to achieve the speed regulation with the consideration of avoiding singularity and improving power efficiency, rotor angular speed and flux amplitude tracking objectives are formulated. rotor resistance uncertainty is compensated by adaptive backstepping and mechanical lumped uncertainty such as load torque disturbance, inertia moment, friction by RBFN. Simulation is provided to verify the effectiveness of the proposed approach.

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Simulation of the Air Conditioning System Using Fuzzy Logic Control

  • Mongkolwongrojn, M.;Sarawit, W.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2270-2273
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    • 2003
  • Fuzzy logic control has been widely implemented in air conditioning and ventilation systems which has uncertainty or high robust system. Since the dynamic behaviors of the systems contain complexity and uncertainty in its parameters , several fuzzy logic controllers had been implemented to control room temperature in the field of air conditioning system. In this paper, the fuzzy logic control has been developed to control room temperature and humidity in the precision air conditioning systems. The nonlinear mathematical model was formulated using energy and continuity equations. MATLAB was used to simulate the fuzzy logic control of the multi-variable air conditioning systems. The simulation results show that fuzzy logic controller can reduce the steady-state errors of the room temperature and relative humidity in multivariable air conditioning systems. The offset are less than 0.5 degree Celsius and 3 percent in relative humidity respectively under random step disturbance in heating load and moisture load respectively

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Reliability analysis of uncertain structures using earthquake response spectra

  • Moustafa, Abbas;Mahadevan, Sankaran
    • Earthquakes and Structures
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    • v.2 no.3
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    • pp.279-295
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    • 2011
  • This paper develops a probabilistic methodology for the seismic reliability analysis of structures with random properties. The earthquake loading is assumed to be described in terms of response spectra. The proposed methodology takes advantage of the response spectra and thus does not require explicit dynamic analysis of the actual structure. Uncertainties in the structural properties (e.g. member cross-sections, modulus of elasticity, member strengths, mass and damping) as well as in the seismic load (due to uncertainty associated with the earthquake load specification) are considered. The structural reliability is estimated by determining the failure probability or the reliability index associated with a performance function that defines safe and unsafe domains. The structural failure is estimated using a performance function that evaluates whether the maximum displacement has been exceeded. Numerical illustrations of reliability analysis of elastic and elastic-plastic single-story frame structures are presented first. The extension of the proposed method to elastic multi-degree-of-freedom uncertain structures is also studied and a solved example is provided.

Unit Commitment for an Uncertain Daily Load Profile (불확실한 부하곡선에 대한 발전기 기동정지계획)

  • 박정도;박상배
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.53 no.6
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    • pp.334-339
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    • 2004
  • In this study, a new UC (Unit Commitment) algorithm is proposed to consider the uncertainty of a daily load profile. The proposed algorithm calculates the UC results with the lower load level than the one generated by the conventional load forecast and the more hourly reserve allocation. In case of the worse load forecast, the deviation of the conventional UC solution can be overcome with the proposed method. The proposed method is tested with sample systems, which shows that the new UC algorithm yields completely feasible solution even though the worse load forecast is applied. Also, the effects of the uncertain hourly load demand are statistically analyzed especially by the consideration of the average over generation and the average under generation. Finally, it is shown that independent power producers participating in electricity spot-markets can establish bidding strategies by means of the statistical analysis. Therefore, it is expected that the proposed method can be used as the basic guideline for establishing bidding strategies under the deregulation power pool.

Uncertainty Observer using the Radial Basis Function Networks for Induction Motor Control

  • Huh, Sung-Hoe;Lee, Kyo-Beum;Ick Choy;Park, Gwi-Tae;Yoo, Ji-Yoon
    • Journal of Power Electronics
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    • v.4 no.1
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    • pp.1-11
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    • 2004
  • A stable adaptive sensorless speed controller for three-level inverter fed induction motor direct torque control (DTC) system using the radial-basis function network (RBFN) is presented in this paper. Torque ripple in the DTC system for high power induction motor could be drastically reduced with the foregoing researches of switching voltage selection and torque ripple reduction algorithms. However, speed control performance is still influenced by the inherent uncertainty of the system such as parametric uncertainty, external load disturbances and unmodeled dynamics, and its exact mathematical model is much difficult to be obtained due to their strong nonlinearity. In this paper, the inherent uncertainty is approximated on-line by the RBFN, and an additional robust control term is introduced to compensate for the reconstruction error of the RBFN instead of the rich number of rules and additional updated parameters. Control law for stabilizing the system and adaptive laws for updating both of weights in the RBFN and a bounding constant are established so that the whole closed-loop system is stable in the sense of Lyapunov, and the stability proof of the whole control system is presented. Computer simulations as well as experimental results are presented to show the validity and effectiveness of the proposed system.

Probabilistic Load Analysis for Tailplane Considering Uncertainties in Design Variables (설계변수의 불확실성을 고려한 미익 하중의 확률론적 해석)

  • Choi, Yong-Joon;Kim, In-Gul;Lee, Seok-Je
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.6
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    • pp.1043-1050
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    • 2010
  • This paper examined the probabilistic load analysis for the tailplane during pitching maneuvering in the conceptual aircraft design phase. The flight load analysis based on the probabilistic distribution of design variables are compared with the results of the deterministic analysis. Two forms of variable distribution are used in this paper. One is standard normal distribution, the other distribution is calculated from the results of short-period longitudinal equation of aircraft motion. The influence of the distribution parameter on the probabilistic load analysis was investigated and the significant design variables that have an impact on the mean and variance of probabilistic load were identified. The comparison indicates that probabilistic load analysis provides more reliable probabilistic load distribution for the structural design than the traditional deterministic analysis.

Reliability analysis of LNG unloading arm considering variability of wind load (풍하중의 변동성을 고려한 LNG 하역구조물의 신뢰성해석)

  • Kim, Dong Hyawn;Lim, Jong Kwon;Koh, Jae Pil
    • Journal of Korean Society of Steel Construction
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    • v.19 no.2
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    • pp.223-231
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    • 2007
  • Considering wind speed uncertainty, reliability analysis of the LNG unloading arm at Tongyoung Production Site was performed. Extreme distribution of wind speed was estimated from the data collected at the weather center and wind load was calculated using wind velocities and coefficients of wind pressure. The unloading arm was modeled with plate and solid elements. Contact elements were used to describe the interface between base of structure andground. Response surface for maximum effective stress was found for reliability analysis and then reliability functions was defined and used to determine exceeding probability of allowable and yield stresses. In addition, sensitivity analysis was also performed to estimate the effect of possible material deterioration in the future.

Concurrent topology optimization of composite macrostructure and microstructure under uncertain dynamic loads

  • Cai, Jinhu;Yang, Zhijie;Wang, Chunjie;Ding, Jianzhong
    • Structural Engineering and Mechanics
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    • v.81 no.3
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    • pp.267-280
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    • 2022
  • Multiscale structure has attracted significant interest due to its high stiffness/strength to weight ratios and multifunctional performance. However, most of the existing concurrent topology optimization works are carried out under deterministic load conditions. Hence, this paper proposes a robust concurrent topology optimization method based on the bidirectional evolutionary structural optimization (BESO) method for the design of structures composed of periodic microstructures subjected to uncertain dynamic loads. The robust objective function is defined as the weighted sum of the mean and standard deviation of the module of dynamic structural compliance with constraints are imposed to both macro- and microscale structure volume fractions. The polynomial chaos expansion (PCE) method is used to quantify and propagate load uncertainty to evaluate the objective function. The effective properties of microstructure is evaluated by the numerical homogenization method. To release the computation burden, the decoupled sensitivity analysis method is proposed for microscale design variables. The proposed method is a non-intrusive method, and it can be conveniently extended to many topology optimization problems with other distributions. Several numerical examples are used to validate the effectiveness of the proposed robust concurrent topology optimization method.

Nonlinear finite element based parametric and stochastic analysis of prestressed concrete haunched beams

  • Ozogul, Ismail;Gulsan, Mehmet E.
    • Structural Engineering and Mechanics
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    • v.84 no.2
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    • pp.207-224
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    • 2022
  • The mechanical behavior of prestressed concrete haunched beams (PSHBs) was investigated in depth using a finite element modeling technique in this study. The efficiency of finite element modeling was investigated in the first stage by taking into account a previous study from the literature. The first stage's findings suggested that finite element modeling might be preferable for modeling PSHBs. In the second stage of the research, a comprehensive parametric study was carried out to determine the effect of each parameter on PSHB load capacity, including haunch angle, prestress level, compressive strength, tensile reinforcement ratio, and shear span to depth ratio. PSHBs and prestressed concrete rectangular beams (PSRBs) were also compared in terms of capacity. Stochastic analysis was used in the third stage to define the uncertainty in PSHB capacity by taking into account uncertainty in geometric and material parameters. Standard deviation, coefficient of variation, and the most appropriate probability density function (PDF) were proposed as a result of the analysis to define the randomness of capacity of PSHBs. In the study's final section, a new equation was proposed for using symbolic regression to predict the load capacity of PSHBs and PSRBs. The equation's statistical results show that it can be used to calculate the capacity of PSHBs and PSRBs.