Robust fault estimation of discrete‐time nonlinear plants via a comprehensive partition‐based switching scheme

This paper presents the design and implementation of an application-specific integrated circuit (ASIC) for a discrete-time current control and space-vector pulse-width modulation (SVPWM) with asymmetric five-segment switching scheme for AC motor drives. As compared to a conventional three-phase symmetric seven-segment switching SVPWM scheme, the proposed method involves five-segment two-phase switching in each switching period, so the inverter switching times and power loss can be reduced by 33%. In addition, the produced PWM signal is asymmetric with respect to the center-symmetric triangular carrier wave, and the voltage command signal from the discrete-time current control output can be given in each half period of the PWM switching time interval, hence increasing the system bandwidth and allowing the motor drive system with better dynamic response. For the verification of the proposed SVPWM modulation scheme, the current control function in the stationary reference frame is also included in the design of the ASIC. The design is firstly verified by using PSIM simulation tool. Then, a DE0-nano field programmable gate array (FPGA) control board is employed to drive a 300W permanent-magnet synchronous motor (PMSM) for the experimental verification of the ASIC.

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Resilient Actuator Fault Estimation for Discrete-Time Complex Networks: A Distributed Approach

IEEE Transactions on Automatic Control ◽

10.1109/tac.2020.3033710 ◽

2020 ◽

pp. 1-1

Author(s):

Yang Liu ◽

Zidong Wang ◽

Donghua Zhou

Keyword(s):

Complex Networks ◽

Discrete Time ◽

Fault Estimation ◽

Actuator Fault ◽

Distributed Approach

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Fault estimation and fault tolerant control for discrete-time nonlinear systems with perturbation by a mixed design scheme

Journal of the Franklin Institute ◽

10.1016/j.jfranklin.2020.12.024 ◽

2020 ◽

Author(s):

Ximing Yang ◽

Tieshan Li ◽

Yue Wu ◽

Yang Wang ◽

Yue Long

Keyword(s):

Nonlinear Systems ◽

Discrete Time ◽

Fault Tolerant ◽

Fault Tolerant Control ◽

Fault Estimation ◽

Mixed Design ◽

Design Scheme

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Gain-Scheduling Fault Estimation for Discrete-Time Takagi-Sugeno Fuzzy Systems: A Depth Partitioning Approach

IEEE Transactions on Circuits and Systems I Regular Papers ◽

10.1109/tcsi.2021.3135911 ◽

2021 ◽

pp. 1-11

Author(s):

Xiangpeng Xie ◽

Daoguang Ma ◽

Dong Yue ◽

Jianwei Xia

Keyword(s):

Discrete Time ◽

Fuzzy Systems ◽

Gain Scheduling ◽

Fault Estimation ◽

Takagi Sugeno

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Observer Design for Simultaneous State and Fault Estimation for a Class of Discrete-time Descriptor Linear Models

E3S Web of Conferences ◽

10.1051/e3sconf/202122901020 ◽

2021 ◽

Vol 229 ◽

pp. 01020

Author(s):

Kaoutar Ouarid ◽

Abdellatif El Assoudi ◽

Jalal Soulami ◽

El Hassane El Yaagoubi

Keyword(s):

Discrete Time ◽

Linear Models ◽

Estimation Error ◽

Equivalent Form ◽

Observer Design ◽

Fault Estimation ◽

Linear Matrix ◽

Sensor Faults ◽

Actuator Faults ◽

Algebraic Equations

This paper investigates the problem of observer design for simultaneous states and faults estimation for a class of discrete-time descriptor linear models in presence of actuator and sensor faults. The idea of the present result is based on the second equivalent form of implicit model [1] which permits to separate the differential and algebraic equations in the considered singular model, and the use of an explicit augmented model structure. At that stage, an observer is built to estimate simultaneously the unknown states, the actuator faults, and the sensor faults. Next, the explicit structure of the augmented model is established. Then, an observer is built to estimate simultaneously the unknown states, the actuator faults, and the sensor faults. By using the Lyapunov approach, the convergence of the state estimation error of the augmented system is analyzed, and the observer’s gain matrix is achieved by solving only one linear matrix inequality (LMI). At long last, an illustrative model is given to show the performance and capability of the proposed strategy.

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