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Comparison of Uncertainties in Membership Function of Adaptive Lyapunov NeuroFuzzy-2 for Damping Power Oscillations
Abstract
The direct focus of this chapter is to explore the potential of online Adaptive NeuroFuzzy Type-2 (ANFT2) control system for damping inter-area oscillations using Static Synchronous Compensator (STATCOM). The nonlinear ANFT2-based direct control scheme is proposed to damp inter-area oscillations by utilizing its model free and universal approximation capabilities. The Gaussian and triangular membership functions with different variations of uncertain mean and standard deviation are considered for ANFT2. The adaptation mechanism utilizes gradient descent-based back-propagation algorithm using Lyapunov stability criteria to update the rule parameters. The performance evaluation of proposed control strategy has been validated using two and three machine power systems. The nonlinear time domain simulations reveal that ANFT2 has excellent damping capabilities as compared to conventional PI control. Simulation results for different performance indices further emphasize the optimal performance of ANFT2 with uncertain mean and variance of triangular membership function in transient and steady state region.
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