• Journal of IKEEE
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• v.7 no.2 s.13
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• pp.156-165
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• 2003

This paper describes the design of a robust adaptive fuzzy observer for uncertain nonlinear dynamical system. We propose a new method in which no strictly positive real (SPR) condition is needed. No a priori knowledge of an upper bound on the lumped uncertainty is required. The Lyapunov synthesis approach is used to guarantee a semi-global uniform ultimate boundedness property of the state observation error, as well as of all other signals in the closed-loop system. The theoretical results are illustrated through a simulation example of a mass-spring-damper system.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.117-127
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• 1998

Power systems have uncertain dynamics due to a variety of effects such as lightning, severe storms and equipment failures. The variation of the effective reactance of a transmission line due to a fault is an example of uncertainty in power system dynamics. Hence, a robust controller to cope with these uncertainties is needed. Recently, fuzzy controllers are becoming quite popular for robust control due to its potential of dealing with uncertain systems. Thus in this paper we design an adaptive fuzzy controller based on an input-output linearization approach for the transient stabilization and voltage regulation of a power system under a sudden fault. Also this paper proposes a fuzzy system that estimates the upper bound of uncertain term in the system dynamics to guarantee the Lyapunov stability. Simulation results show that good performance is achieved by the proposed controller.

• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.697-708
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• 2014

The intentional buckling design of micro-films has various potential applications in engineering. The buckling amplitude and critical strain of micro-films are the crucial parameters for the buckling design. In the reported studies, the film parameters were regarded as deterministic. However, the geometrical and physical parameters uncertainty of micro-films due to manufacturing becomes prominent and needs to be considered. In the present paper, the probabilistic nonlinear buckling analysis of micro-films with uncertain parameters is proposed for design accuracy and reliability. The nonlinear differential equation and its asymptotic solution for the buckling micro-film with nominal parameters are firstly established. The mean values, standard deviations and variation coefficients of the buckling amplitude and critical strain are calculated by using the probability densities of uncertain parameters such as the film span length, thickness, elastic modulus and compressive force, to reveal the effects of the film parameter uncertainty on the buckling deformation. The results obtained illustrate the probabilistic relation between buckling deformation and uncertain parameters, and are useful for accurate and reliable buckling design in terms of probability.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.10
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• pp.776-782
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• 2006

A new district cooling system using ice slurry for the uncertain cooling load of the future is presented. The chilled water produced by the absorption chillers is used for the base cooling load. The temperature of the chilled water is reduced by mixing of ice slurry depending on increasing of the cooling load. Finally, IF of the ice slurry is increased up to 10% at the peak load. The transporting mass flow rate is decreased down to 44.7%, and the diameter of the main pipe is decreased down to 66.7%, but the diameter of the branched pipe is designed as the same size of the chilled water.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.369-374
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• 2006

Quantification of infiltration rate is an important issue in HVAC system design. The infiltration in buildings depends on many uncertain parameters that vary with significant magnitude and hence, the results from standard deterministic simulation approach can be unreliable. The authors utilize uncertainty analysis In predicting the airflow rates. The paper presents relevant uncertain parameters such as meteorological data, building parameters (leakage areas of windows, doors, etc.), etc. Uncertainties of the aforementioned parameters are quantified based on available data from literature. Then, the Latin Hypercube Sampling (LHS) method was used for the uncertainty propagation. The LHS is one of the Monte Carlo simulation techniques that is suited for our needs. The CONTAMW was chosen to simulate infiltration phenomena in a residential apartment that is typical of residential buildings in Korea. It will be shown that the uncertainty propagating through this process is not negligible and may significantly influence the prediction of the airflow rates.

• Coupled systems mechanics
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• v.7 no.6
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• pp.707-729
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• 2018

The semi-active optimal vibration control of nonlinear torsion-bar suspension vehicle systems under random road excitations is an important research subject, and the boundedness of MR dampers and the uncertainty of vehicle systems are necessary to consider. In this paper, the differential equations of motion of the coupling torsion-bar suspension vehicle system with MR damper under random road excitation are derived and then transformed into strongly nonlinear stochastic coupling vibration equations. The dynamical programming equation is derived based on the stochastic dynamical programming principle firstly for the nonlinear stochastic system. The semi-active bounded parametric optimal control law is determined by the programming equation and MR damper dynamics. Then for the uncertain nonlinear stochastic system, the minimax dynamical programming equation is derived based on the minimax stochastic dynamical programming principle. The worst-case disturbances and corresponding semi-active bounded parametric optimal control are obtained from the programming equation under the bounded disturbance constraints and MR damper dynamics. The control strategy for the nonlinear stochastic vibration of the uncertain torsion-bar suspension vehicle system is developed. The good effectiveness of the proposed control is illustrated with numerical results. The control performances for the vehicle system with different bounds of MR damper under different vehicle speeds and random road excitations are discussed.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.948-958
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• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• Journal of applied mathematics & informatics
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• v.40 no.1_2
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• pp.351-370
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• 2022

The design of mechanical structures aims to meet criteria, together with the safety of operators and lives in the vicinity of the equipment. Thus, there are several cases that meeting the desired specification causes the mechanical device to perform unstable and, sometimes, chaotic behavior. In these cases, control methods are applied in order to stabilize the device when in operation, aiming at the physical integrity of the component and the device operators. In this work, we will develop a study about the influence of a controller applied in a non-ideal capsule system operating with uncertain parameters, being non-existent in the literature. For this, two initial conditions were used: one that the capsule starts from rest and another that it is already in motion. Thus, the effectiveness of the controller can be assessed in both initial conditions, restricting the movement of the internal vibration-impact system to the capsule.

• Structural Engineering and Mechanics
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• v.87 no.3
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• pp.231-242
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• 2023

A novel combinatorial type-2 adaptive neuro-fuzzy inference system (T2-ANFIS) and robust proportional integral derivative (PID) control framework for intelligent vibration mitigation of uncertain structural system is introduced. The fuzzy logic controllers (FLCs), are designed independently of the mathematical model of the system. The type-1 FLCs, have a limited ability to reduce the effect of uncertainty, due to their fuzzy sets with a crisp degree of membership. In real applications, the consequent part of the fuzzy rules is uncertain. The type-2 FLCs, are robust to the fuzzy rules and the process parameters due to the fuzzy degree of membership functions and footprint of uncertainty (FOU). The adaptivity of the proposed method is provided with the optimum tuning of the parameters using the neural network training algorithms. In our approach, the PID control force is obtained using the generalized type-2 neuro-fuzzy in such a way that the stability and robustness of the controller are guaranteed. The robust performance and stability of the presented framework are demonstrated in a numerical study for an eleven-story seismically-excited building structure combined with an active tuned mass damper (ATMD). The results indicate that the introduced type-2 neuro-fuzzy PID control scheme is effective to attenuate plant states in the presence of the structured and unstructured uncertainties, compared to the conventional, type-1 FLC, type-2 FLC, and type-1 neuro-fuzzy PID controllers.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.107-110
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• 2013

Recently, Korea parliament legislated the Low Carbon Green Growth Act (April, 2012) and approved a bill (May, 2012) to start carbon emission trading system in 2015. It means that for the first time, government would regulate the amounts of carbon emission in private entities, and private entities should attain predefined emission reduction goals by implementing clean development mechanism (CDM) project or buy the Certified Emission Reductions (CERs) from the trading market to avoid penalty. Under these circumstances, it is not easy for them to determine when or how to implement the CDM project because the governmental energy policies about the level of governmental subsidies, periods for free emission allocation, etc. are still under discussion and the future price of the CERs is quite uncertain. Thus, this study presents a real-option based model to assess the financial viability of the CDM project which switches bunker-C oil to liquefied natural gas (LNG). The proposed model is expected to assist private entities in establishing the investment strategy for CDM project under uncertain government energy policies.