Journal of Intelligent & Fuzzy Systems - Volume 22, issue 4

Authors: Escobet, Antoni | Nebot, Àngela | Cellier, François E.

Article Type: Research Article

Abstract: This paper describes a fault diagnosis system (FDS) for non-linear plants based on fuzzy logic. The proposed approach, named VisualBlock-FIR, runs under the Simulink framework and enables early fault detection, isolation, and identification. During fault detection, the FDS should recognize that the plant behavior is abnormal, and therefore, that the plant is not working properly. During fault isolation/identification, the FDS should conclude, which type of failure has occurred. The enveloping and acceptability measures introduced in VisualBlock-FIR enhance the robustness of the overall process. The proposed approach is used for tackling faults of the DAMADICS benchmark, and the results are compared …with those obtained by other FDS. Show more

DOI: 10.3233/IFS-2011-0473

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 4, pp. 155-171, 2011

Authors: Dang, Thai Viet | Wang, Wen-June | Huang, Cheng-Hao | Sun, Chung-Hsun | Luoh, Leh

Article Type: Research Article

Abstract: The paper proposes a novel fuzzy observer synthesis for the Takagi–Sugeno (T–S) fuzzy system with uncertainty and output disturbance. First, an augmented fuzzy model is built by integrating the system state and the output disturbance into a new variable. Then, based on Lyapunov theory and LMIs tools, two main theorems are derived for particular and general cases of fuzzy systems, respectively. In each main theorem, three key conditions are proposed, under which the fuzzy observer is synthesized to estimate the system state and the output disturbance simultaneously. According to the main theorems, a methodical procedure for the fuzzy observer synthesis …is also provided. Finally, the effectiveness of the observer is demonstrated by a numerical example. Show more

Keywords: Augmented model, fuzzy system models, linear matrix inequalities (LMIs), state observer, uncertainty and disturbance

DOI: 10.3233/IFS-2011-0474

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 4, pp. 173-183, 2011

Authors: Kim, Yeesock | Langari, Reza | Hurlebaus, Stefan

Article Type: Research Article

Abstract: This paper proposes a multi-input, multi-output (MIMO) nonlinear system identification (SI) of civil structures equipped with magnetorheological (MR) dampers. The nonlinear SI model is developed through the integration of multiple MIMO autoregressive exogenous (ARX) input models, Takagi-Sugeno (TS) fuzzy model, weighted linear least squares, fuzzy C-means and subtractive clustering algorithms. To demonstrate the effectiveness of the MIMO ARX-TS fuzzy model, a seismically excited three-story building equipped with an MR damper is investigated: Parameters of the premise and consequent parts for the proposed model are represented in detail and comparison between the original data and identified one is given. It is …shown from the simulation that the proposed nonlinear MIMO ARX-TS fuzzy identification algorithm is effective in estimating nonlinear behavior of a seismically excited building-MR damper system. Show more

Keywords: Multi-input, multi-output (MIMO), system identification, autoregressive exogenous (ARX) input models, Takagi-Sugeno (TS) fuzzy model, weighted linear least squares, fuzzy C-means, subtractive clustering, smart structures, structural control, civil structures, earthquake engineering, magnetorheological (MR) damper

DOI: 10.3233/IFS-2011-0482

Citation: Journal of Intelligent & Fuzzy Systems, vol. 22, no. 4, pp. 185-205, 2011