Low-Computation Adaptive Control with Prescribed Performance for Uncertain Switched Nonlinear Systems

A low-computation adaptive output-feedback prescribed performance control method is presented for a family of strict-feedback uncertain switched nonlinear systems with unmeasurable states and disturbances. Firstly, different observers are designed for subsystems to estimate the unknown states while reducing conservatism. Secondly, by using a modified tuning function, the prescribed performance control is attained within a finite time, while alleviating stringent initial condition requirements. Then a low-computation adaptive controller is designed, which effectively circumvents issues related to approximation techniques and analytical derivatives. Furthermore, only a set of adaptive laws is needed, significantly reducing the number of parameters and computational burden. The overall framework integrates backstepping with tangent barrier Lyapunov function to demonstrate the stability of the closed- loop system. Finally, simulation experiment demonstrates the effectiveness of the given control strategy.