A new model reference adaptive control with arbitrary nonlinear inputs

This paper presents a new analysis method for model reference adaptive control(MRAC) with arbitrary bounded input nonlinearities. The reduced-order plant is assumed to be of an arbitrary relative degree. In the absence of un-modeled dynamics and bounded disturbances, the tracking error depends on input nonlinearities. A new modified MRAC scheme is also proposed to improve the transient and steady state performances. The output error is used directly in the control law to generate a modified control signal to compensate possible bad performances of the robust adaptive controllers, and the ideal asymptotic properties of MRAC is not destroyed.