Abstract
A novel adaptive control strategy to control the nonlinear dynamic plants is proposed in this article. The proposed Hybrid Adaptive NeuroFuzzy Bspline based Wavelet Control (HABsWC) synergistically integrates the locally controllable Bspline membership functions and wavelets in the NeuroFuzzy architecture. The parameters of HABsWC are updated online using gradient descent based backpropagation algorithm and the stability is guaranteed by defining an upper bound on the learning rates using Lyapunov stability criteria. Some important considerations are presented highlighting the effectiveness of online sensitivity measure of plant in adaptive control law. By providing online sensitivity measure, the adaptive control law influences the convergence of system states and smoothness of control effort. Electric power system, being highly nonlinear and non-stationary in nature, has been chosen as a plant for the application of HABsWC to damp power system oscillations using Static Synchronous Series Compensator (SSSC). The performance of the proposed control scheme is validated using different operating conditions and faults for Single Machine Infinite Bus (SMIB) test system. The performance comparison, based on nonlinear time domain simulations and different performance indices, reveals that the proposed control strategy improves the performance of SSSC to enhance the transient stability with increase in smoothness of control effort.