A novel multiple adaptive fuzzy system for robust nonlinear control

A novel approach using multiple adaptive fuzzy systems for controlling complex nonlinear systems for improved transient response, is developed in this study. The multiple adaptive fuzzy controllers are soft-switched depending on the operating conditions using another fuzzy-based function. Apart from that, a single adaptive fuzzy controller is also developed for comparison studies. These fuzzy setups are used separately in pursuit of robust compensation for the unmodeled dynamics, nonlinearity issues, external disturbances and model uncertainties etc., thus ensuring a globally asymptotically stable system. A Lyapunov-based Kalman-Yakubovich-Popov (KYP) lemma is used to ensure closed loop robust stability of the control systems with the establishment of positive-realness of the error system. A simulation study using a passenger car model, an example of complex nonlinear system, is carried out. The results obtained from these simulation studies demonstrate that the multiple adaptive controller setup results in substantial improvements over the single adaptive system especially in the transient effects with the performance of complex systems.