Fuzzy Control of Nonlinear Systems with Input Saturation Using Multiple Model Structure

For a class of nonlinear systems with input saturation, a kind of adaptive fuzzy control law based on multiple-model structure is presented in this paper. First, a basic fuzzy controller is designed with adaptive weight parameters determined by multiplemodel switching performance indexes. Then a dynamic structure adaptive neural network is introduced for ensuring the system stable, while the control hedging scheme is also adopted to prevent the system from being influenced by the actuator saturation and maintain working normally. Finally, the simulation results show the control method presented is effective by demonstrating the full envelope tracking control for a puddle-jumper.