• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.1-5
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• 2006

This paper deals with a fault detection system design for uncertain nonlinear systems modelled as T-S fuzzy systems with the integral quadratic constraints. In order to generate a residual signal, we used a left coprime factorization of the T-S fuzzy system. From the filtered signal of the residual generator, the fault occurence can be detected effectively. A simulation study with nuclear steam generator level control system shows that the suggested method can be applied to detect the fault in actual applications.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.2
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• pp.87-93
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• 2009

Intrusion tolerant system enables essential services to maintain for a period of time under system failure, malicious attacks and is gaining more importance in national defense, communication infrastructure, and financial sector. However, few objective evaluation criteria for companies and agencies to introduce an appropriate system are available. This paper proposes a suitability evaluation method, using Analytic hierarchy process and fuzzy integral, for intrusion tolerant system, along with evaluation criteria which considers the characteristics and costs of systems in addition to other factors.

• Journal of Korean Port Research
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• v.7 no.1
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• pp.13-24
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• 1993

The rapid progress of the intermodal freight transportation in recent years has induced fierce competition among the adjacent hub ports for container transport. This brings increased attention to the evaluation of the port competitive ability. But it is not easy to evaluate the port competitive ability because this belongs to ill-defined system which is composed of ambiguous interacting attributes. Paying attention to this point, this paper deals the competitive ability of container port in Far-East Asia by fuzzy integral evaluation which is adequate to interacting ambiguous attribute problem. For this, the proposed fuzzy evaluation algorithm is applied to the real problem, based on the factors such as cargo volumes, costs, services, infrastructure and geographical sites These are extracted from the precedent study of port competitive ability, etc. The results show that the port evaluation factors come in following order ; services, costs, infrastructure, geographical sites and cargo volumes. There are some interactions(interaction coefficient, ${\lambda}=-0.664$ between evaluation attributes. The port competitive ability comes in following order : Singapore, Hongkong, Kobe, Kaoshiung and Busan. According to the sensitivity analysis, the rank between Busan and Kaoshiung changes when ${\lambda}=0.7$. From the analysis of the results, we confirmed that the proposed fuzzy evaluation algorithm is very effective in the complex-fuzzy problem which is composed of hierarchical structure with interacting attributes.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.905-913
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• 2017

Advanced reactor designs often feature longer operating cycles between refueling and new concepts of operation beyond traditional baseload electricity production. Owing to this increased complexity, traditional proportional-integral control may not be sufficient across all potential operating regimes. The prototypical advanced reactor (PAR) design features two independent reactor modules, each connected to a single dedicated steam generator that feeds a common balance of plant for electricity generation and process heat applications. In the current research, the PAR is expected to operate in a load-following manner to produce electricity to meet grid demand over a 24-hour period. Over the operational lifetime of the PAR system, primary and intermediate sodium pumps are expected to degrade in performance. The independent operation of the two reactor modules in the PAR may allow the system to continue operating under degraded pump performance by shifting the power production between reactor modules in order to meet overall load demands. This paper proposes a Takagi-Sugeno (T-S) fuzzy logic-based power distribution system. Two T-S fuzzy power distribution controllers have been designed and tested. Simulation shows that the devised T-S fuzzy controllers provide improved performance over traditional controls during daily load-following operation under different levels of pump degradation.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.504-506
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• 1999

In this paper, we propose a method which control parametric uncertainty systems using PID controller by fuzzy auto tuning. We get the error and the error change rate of plant output correspond to the initial value of parameter using the Ziegler-Nickols tuning and determine the new proportional gain$(K_p)$ and the integral time $(T_i)$ from fuzzy tuner by the error and error change rate of plant output as a membership function of fuzzy theory. The Fuzzy Auto-tuning algorithm for PID controller operate to adapt variable parameter of plant in parametric uncertainty systems. It is shown this method considerably improve the transient response at computer simulation.

• Journal of Power Electronics
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• v.8 no.2
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• pp.141-147
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• 2008

This paper deals with a new and improved control technique for shunt active filters (AF) used for compensating unwanted harmonic currents injected in the mains due to nonlinear varying loads. This work is motivated by the need to find a permanent solution to the rigorous hit and trial method for evaluating system parameters in an indirect control of AF. A fuzzy pre-compensated PI (Proportional-Integral) controller is used to fuzzify the reference DC voltage of AF to the controller input so that the overshoots and undershoots in its DC link voltage are minimized and the settling time is improved. A three-phase diode rectifier with R-L (Resistive-Inductive) load is used as a non-linear load to study the effectiveness of the proposed controller of the AF. Robustness to filter parameter variations, insensitivity to controller parameter variations, and transient response has been taken as performance evaluation parameters. The results are shown through simulations in Matlab using power system block sets to demonstrate the capability of the proposed controller of the AF.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1101-1105
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• 2012

This study proposes a method for improvement of PD type fuzzy controller. The method includes self tuner using gradient algorithm that is one of the optimization algorithms. The proposed controller improves simple Takagi-Sugeno type FLC (Fuzzy Logic Control) system. The simple Takagi-Sugeno type FLC system changes nonlinear characteristic to linear parameters of consequent membership function. The simple FLC system could control the system by calibrating parameter of consequent membership function that changes the system response. While the determination on parameter of the simple FLC system works well only partially, the proposed method is needed to determine parameters that work for overall response. The simple FLC system doesn't predict the response characteristics. While the simple FLC system works just like proportional part of PID, our system includes derivative part to predict the next response. The proposed controller is constructed with P part and D part FLC system that characteristic parameter on system response is changed by self tuner for effective response. Since the proposed controller doesn't include integral part, it can't eliminate steady state error. So we include a gain to eliminate the steady state error.

• 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.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.822-828
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• 2018

AC-DC conversion is a necessary for the systems that require DC source. This conversion has been done via rectifiers based on controlled or uncontrolled semiconductor switches. Advances in the power electronics and microprocessor technologies allowed the use of Pulse Width Modulation (PWM) rectifiers. In this paper, dq-axis current and DC link voltage of three-phase PWM rectifier are controlled by using type-2 fuzzy neural network (T2FNN) controller. For this aim, a simulation model is built by MATLAB/Simulink software. The model is tested under three different operating conditions. The parameters of T2FNN is updated online by using back-propagation algorithm. The results obtained from both T2FNN and Proportional + Integral + Derivate (PID) controller are given for three operating conditions. The results show that three-phase PWM rectifier using T2FNN provides a superior performance under all operating conditions when compared with PID controller.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.595-604
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• 2011

A three-phase three-level shunt active filter controlled by fuzzy logic current controller which can compensate current harmonics generated by nonlinear loads is presented. Three-level inverters and fuzzy controllers have been successfully employed in several power electronic applications these past years. To improve the conventional pwm controller performance, a new control scheme based on fuzzy current controller is adopted for three-level (NPC) shunt active filter. The scheme is designed to improve compensation capability of APF by adjusting the current error using a fuzzy rule. The inverter current reference signals required to compensate harmonic currents use the synchronous reference detection method. This technique is easy to implement and achieves good results. To maintain the dc voltage across capacitor constant and reduce inverter losses, a proportional integral voltage controller is used. The simulation of global system control and power circuits is performed using Matlab-Simulink and SimPowerSystem toolbox. The results obtained in transient and steady states under various operating conditions show the effectiveness of the proposed shunt active filter based on fuzzy current controller compared to the conventional scheme.