State tracking model reference adaptive control for switched nonlinear systems with linear uncertain parameters

Model reference adaptive control (MRAC) is considered for a class of switched nonlinear systems in which the unknown parameters appear linearly. The linear uncertain parameters in each subsystem can be expressed as a vector and the uncertain vectors in different subsystems are estimated individually by different vector variables. Update laws are designed such that the parameter estimation will ‘freeze’ until its corresponding subsystem is active. Controllers for subsystems are given to ensure asymptotic states tracking under arbitrary switchings. Two examples are presented to validate the proposed method.