• 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.

• Korean Journal of Adult Nursing
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• v.23 no.1
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• pp.20-30
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• 2011

Purpose: The aim of this study was to examine patients with Chronic Hepatitis B (CHB) and their level of knowledge of their disease, uncertainty, stress and health behaviors and to identify factors influencing their health behavior. Methods: A cross-sectional, descriptive design was used. The sample included 136 patients in a gastroenterology outpatient department at one hospital located in Seoul. The mean age of the subjects was 41 and 77.2% were male. Data were collected using a structured questionnaire from April to June 2009. The collected data were analyzed using SPSS/WIN 15.0. Results: The reported scores for knowledge of the disease, uncertainty, stress, and health behaviors were 14.43, 81.50, 26.50, 52.11, respectively. There were statistically difference between health behaviors and gender, age, marital status and antivirus treatment. A positive correlation existed between knowledge of disease and health behaviors (r=.199, p=.020). In contrast, there was a negative correlation between uncertainty and health behaviors (r=-.250, p=.003). The factors influencing health behaviors were knowledge of disease, gender, age, uncertainty, antivirus treatment, and marital status ($R^2$=.267, p<.001). Conclusion: These findings support that strategies for enhancing knowledge of disease and reducing uncertainty are needed to promote health behavior in patients with CHB.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.109-112
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• 1997

In this note, we investigate a noniterative design method of an observer-based robust H$\_$2/ controller in the presence of structured real parameter uncertainty by applying Riccati approach based on the guaranteed cost function. Motivated by the numerical difficulty of the problem, we try to develop a simple design method named as block-diagonal approach, which can be solved by the LMIs method. By assuming the block-diagonal structure of Riccati solution, the original problem can be derived into two sequentially decoupled optimization problems as LQG control problem. The proposed method seems to be numerically efficient in obtaining a feasible compensator.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.78-82
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• 2002

In this paper, we have studied a numerical stability analysis method for the robust fuzzy feedback linearization regulator using Takagi-Sugeno fuzzy model. To analyze the robust stability, we assume that uncertainty is included in the model structure with known bounds. For these structured uncertainty, the robust stability of the closed system is analyzed by applying Linear Matrix Inequalities theory following a transformation of the closed loop systems into Lur'e systems.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.275-278
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• 2001

Research on the forced vibration control of a flexible GFR composite beam using $\mu$-synthesis is performed on this paper. Modal analysis method and modal coordinates are introduced to obtain the state equations of the structural system. Using these equations, Robust control algorithm using $\mu$-synthesis is adopted to suppress the forced vibration of a flexible beam since the designed controller can considered plant uncertainty and external disturbance. Constant disturbance which is generated by shaking the flexible beam as I's natural frequency is effectively rejected by a PZT actuator. Simulations and experiments are carried out with the designed controller and effectiveness of forced vibration suppression strategy is verified by results.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.356-362
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• 2002

In this paper, well-known Takagi-Sugeno fuzzy model is used as the nonlinear plant model and uncertainty is assumed to be included in the model structure with known bounds. Based on the fuzzy models, a numerical robust stability analysis for the fuzzy feedback linearization regulator is presented using Linear Matrix Inequalities (LMI) Theory. For these structured uncertainty, the closed system can be cast into Lur'e system by simple transformation. From the LMI stability condition for Lur'e system, we can derive the robust stability condition for the fuzzy feedback linearization regulator based on Takagi-Sugeno fuzzy model. The effectiveness of the proposed analysis is illustrated by a simple example.

• Journal of Korean Society for Quality Management
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• v.33 no.1
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• pp.64-72
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• 2005

The ever increasing demand for enhanced competitiveness of engineered products requires "designing-in-quality" strategies that can effectively and efficiently incorporate concepts of uncertainty and quality into design. Multi-attribute utility function is commonly used to represent the decision-maker's preference on multiple design attributes under conditions of uncertainty and risk. One of the major issues in implementing this approach concerns the generation of appropriate utility function, especially in a complex engineering design environment. Typically, the decision maker's preference is revealed through lottery questions rather than being structured on the deductive reasoning to reflect the nonlinear tradeoffs among the attributes. The use of such intuitive procedures can lead to inexact preference information that may result in inaccuracy and rank reversal problems. This paper presents an alternative procedure based on the pair-wise comparisons between design alternatives towards a consistent preference presentation in assessing multiplicative utility function. The effectiveness of the overall procedures is tested with the aid of an injection-molding process design for a capacitor can and the results are discussed.

• Journal of Electrical Engineering and information Science
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• v.2 no.4
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• pp.28-36
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• 1997

In this paper, robust stability analysis for the fuzzy feedback linearization regulator is presented. Well-known Takagi-Sugeno fuzzy model is used as the MISO nonlinear plant model. Uncertainty and disturbance are assumed to be included in the model structure with known bounds. For these structured uncertainty and disturbances, robust stability of the close system is analyzed in both input-output sense and Lyapunov sense. The robust stability conditions are proposed by using multivariable circle criterion and the relationship between input-output stability and Lyapunov stability. The proposed stability analysis is illustrated by a simple example.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.449-451
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• 1998

In this paper, we consider the problem of the robust stability of uncertain linear systems with multiple time-varying delays. The considered uncertainties are both the unstructured uncertainty which is only known its norm bound and the structured uncertainty satisfying the matching conditions, respectively. We present conditions that guarantee the robust stability of systems based on Lyapunov stability theorem and $H_{\infty}$ theory in the time domain. Finally, we show the usefulness of our results by numerical examples.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.1
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• pp.13-19
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• 1995

In this paper, generalized singular value is defined. Using the generalized singular value, robust stability conditions and robust pole placement conditions of structured uncertain systems with star shaped uncertainties are derived. Especially, norm bounded and polytopic uncertainty regions are considered as star shaped uncertainty regions. Linear matrix inequality problems are proposed in order to compute the upper bound of the generalized singular value. The proposed linear matrix inequality problems can be solved by using the convex optimization method.