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Analysis of the fault tolerant induction motor drive system

Klimkowski K., Dybkowski M.

Computer Applications in Electrical Engineering

2014

Vol. 12

302--308

In the paper the influence of the chosen sensors faults (rotor speed and stator current sensors) to the properties of vector controlled induction motor drive system are tested. Faults detection algorithms based on the simple signals from internal control structure are developed. The simulation tests carried out in Matlab/SimPowerSystem software. The proposed solution can be successfully applied in the fault tolerant drive systems.

Observer-based fault-tolerant control against sensor failures for fuzzy systems with time delays

Tong S., Yang G., Zhang W.

International Journal of Applied Mathematics and Computer Science

2011

Vol. 21, no 4

617-627

This paper addresses the problems of robust fault estimation and fault-tolerant control for Takagi-Sugeno (T-S) fuzzy systems with time delays and unknown sensor faults. A fuzzy augmented state and fault observer is designed to achieve the system state and sensor fault estimates simultaneously. Furthermore, based on the information of on-line fault estimates, an observer-based dynamic output feedback fault-tolerant controller is developed to compensate for the effect of faults by stabilizing the resulting closed-loop system. Sufficient conditions for the existence of both a state observer and a fault-tolerant controller are given in terms of linear matrix inequalities. A simulation example is given to illustrate the effectiveness of the proposed approach.

Fault detection using neuro-fuzzy networks

Kowal M., Korbicz J., Mendes M.J., Calado J.M.

Systems Science

2002

Vol. 28, nr 1

45-57

Generally, there methodologies for developing and testing fault detection (FD) algorithms can be distinguished: software benches, hardware benches and industrial data. The current approach uses a hardware bench that consists of process under supervision (two interconnected stations), supervision unit, fault diagnosis unit and fault simulation unit. All elements of the bench are connected to a PROFIBUS network that acts as the communication system exchanging information between automation system and distributed field devices. A realistic and flexible environment for developing and testing FD systems has been constructed using elements commonly used in industry. During the current studies actuator faults, sensor faults and leakages have been considered as incipient and abrupt faults. The proposed FD algorithm is based on neuro-fuzzy models that are responsible for residual generation.