Integrated feature analysis and fuzzy rule-based systemidentification in a neuro-fuzzy paradigm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A systematic study of fuzzy PID controllers-function-based evaluation approach
IEEE Transactions on Fuzzy Systems
The equivalence between fuzzy logic systems and feedforward neural networks
IEEE Transactions on Neural Networks
Neuro-fuzzy rule generation: survey in soft computing framework
IEEE Transactions on Neural Networks
A neuro-fuzzy scheme for simultaneous feature selection and fuzzy rule-based classification
IEEE Transactions on Neural Networks
Differences between t-norms in fuzzy control
International Journal of Intelligent Systems
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The electrical energy has become the major form of energy for end use consumption in today's world. There is always a need of making electric energy generation more economic and reliable. For proper operation, this large integrated system requires a stable operating condition. The power system is a dynamic system. It is constantly being subjected to small disturbances, which cause the generators relative angles to change [A.R. Messina, et al., An investigation on the use of power system stabilizers for damping inter-area oscillations in longitudinal power systems, IEEE Trans. Power Systems 13(2) (1997)]. For the interconnected system to be able to supply the load power demand when the transients caused by disturbance die out, a new acceptable steady state operating condition is reached [A. Soos, An optimal adaptive power system stabilizer, Ph.D. Thesis, University of Calgary, October 1997]. It is important that these disturbances do not drive the system to an unstable condition. The small signal stability problem is associated with modes of oscillations affecting either a single machine (local modes) or a small group of relatively closely connected machines or inter-area (global modes). This problem has got a very high attention in the last three decades and many types of controllers depend on classical and modern control theory have been developed by designing supplementary control signals to improve system damping [A.R. Messina, et al., An investigation on the use of power system stabilizers for damping inter-area oscillations in longitudinal power systems, IEEE Trans. Power Systems 13(2) (1997)]. In this research a novel power system stabilizer for damping both local and global modes of an interconnected system based on neuro fuzzy (hybrid) system is developed. NN-MISO (neural network multiple input single output) is proposed for local modes and Takagi-Sugneo's neuro-fuzzy system is proposed for global modes control [A. Soos, An optimal adaptive power system stabilizer, Ph.D. Thesis, University of Calgary, October 1997]. A comparative study between the proposed controller and most of widely used types of controllers (i.e. optimal controller and lead-lag stabilizer) are made towards damping electromechanical modes of oscillations. The results proved the potency of hybrid controller for power system stability control [D. Chakraborty, N.R. Pal, Integrated feature analysis and fuzzy rule-based system identification in a neuro-fuzzy paradigm, IEEE Trans. Systems Man Cybernet. 31(3) (2001) 391-400].