A novel disturbance rejection factor based stable direct adaptive fuzzy control strategy for a class of nonlinear systems

This paper proposes a unique disturbance rejection factor (DRF) based design of direct stable adaptive fuzzy logic controllers (AFLCs) for a class of non-linear systems with large and fast disturbances. The proposed AFLCs are realized by employing hybrid combinations of Lyapunov theory based local adaptation and harmony search algorithm based global optimization technique. These hybrid AFLCs are designed with the objective of optimizing both the structure and free parameters of it with guaranteed stability and, at the same time, simultaneously achieving satisfactory tracking performance and disturbance rejection. The novelty of the proposed work lies in the fact that, in a bid to perform the disturbance rejection, the nature of the disturbance itself is used in designing the tracking control law. The proposed DRF based hybrid stable AFLCs are implemented for several benchmark case studies and extensive performance evaluations demonstrate their usefulness.

Automated summary

This paper proposes a unique design of direct stable adaptive fuzzy logic controllers for non-linear systems with large and fast disturbances, utilizing a hybrid approach of local adaptation and global optimization. The controllers aim to optimize structure and parameters for stability, tracking performance, and disturbance rejection, using the nature of disturbances in the design process. Implementation in benchmark case studies shows the controllers' effectiveness.