Fault Diagnosis and Fault Tolerant Control for T-S Fuzzy Stochastic Distribution Systems Subject to Sensor and Actuator Faults

被引:50
作者
Wang, Hao [1 ]
Kang, Yunfeng [1 ]
Yao, Lina [1 ]
Wang, Hong [2 ]
Gao, Zhiwei [3 ]
机构
[1] Zhengzhou Univ, Sch Elect Engn, Zhengzhou 450001, Peoples R China
[2] Oak Ridge Natl Lab, Oak Ridge, TN 37830 USA
[3] Univ Northumbria, Newcastle Upon Tyne NE1 8QH, Tyne & Wear, England
关键词
Actuators; Observers; Probability density function; Fuzzy logic; Uncertainty; Fault diagnosis; Fault diagnosis (FD); fault tolerant control (FTC); stochastic distribution control (SDC) systems; sensor and actuator faults; Takagi-Sugeno (T-S) fuzzy model; PRODUCT MODEL REPRESENTATION; PARTICLE-SIZE DISTRIBUTION; TRACKING CONTROL; SHAPE CONTROL; QLPV MODELS; DESIGN; FEASIBILITY;
D O I
10.1109/TFUZZ.2020.3024659
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The problem of fault diagnosis (FD) and fault tolerant control for a class of Takagi-Sugeno (T-S) fuzzy stochastic distribution control systems subject to sensor and actuator faults is discussed in this article. First, fuzzy logic models are used to approximate the output probability density function (PDF). Next, an adaptive augmented state/FD observer is proposed to estimate the system state, sensor and the actuator faults simultaneously. New expected weights based on the sensor fault estimation information and a PI-type fuzzy feedback fault tolerant controller are designed to compensate the effect of sensor fault and actuator fault simultaneously. When the sensor fault occurs, the expected objective is redesigned to compensate the sensor fault. Meanwhile, the PI controller can compensate the effect of actuator fault, and the output PDF of the system can still track the desired PDF after the fault occurs. Finally, an example of quality distribution control in chemical reaction process is given to confirm the effectiveness of the algorithm.
引用
收藏
页码:3561 / 3569
页数:9
相关论文
共 51 条
  • [1] Alegra-Zamudio M., 2011, ISA T, V50, P480
  • [2] [Anonymous], 2000, ADV IND CON
  • [3] Baranyi P., 2016, TP-Model Transformation-Based-Control Design Frameworks
  • [4] Extracting LPV and qLPV Structures From State-Space Functions: A TP Model Transformation Based Framework
    Baranyi, Peter
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2020, 28 (03) : 499 - 509
  • [5] The Generalized TP Model Transformation for T-S Fuzzy Model Manipulation and Generalized Stability Verification
    Baranyi, Peter
    [J]. IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (04) : 934 - 948
  • [6] Carbot-Rojas DA, 2019, INT CONF SYST THEO, P43, DOI [10.1109/ICSTCC.2019.8885567, 10.1109/icstcc.2019.8885567]
  • [7] Sensor fault estimation and compensation for time-delay switched systems
    Du, Dongsheng
    Jiang, Bin
    Shi, Peng
    [J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2012, 43 (04) : 629 - 640
  • [8] Sensor fault detection and isolation via high-gain observers: Application to a double-pipe heat exchanger
    Escobar, R. F.
    Astorga-Zaragoza, C. M.
    Tellez-Anguiano, A. C.
    Juarez-Romero, D.
    Hernandez, J. A.
    Guerrero-Ramirez, G. V.
    [J]. ISA TRANSACTIONS, 2011, 50 (03) : 480 - 486
  • [9] Escobar RF., 2016, CHEM ENG COMMUN, V204, P1
  • [10] Guo L, 2010, ADV IND CONTROL, P1, DOI 10.1007/978-1-84996-030-4