A Robust Nonlinear Model Reference Adaptive Control for Disturbed Linear Systems: An LMI Approach

In this article, a robust nonlinear model reference adaptive control (MRAC) is proposed for disturbed linear systems, i.e., linear systems with parameter uncertainties, and external time-dependent perturbations or nonlinear unmodeled dynamics matched with the control input. The proposed nonlinear control law is composed of two nonlinear adaptive gains. Such adaptive gains allow the control to counteract the effects of some perturbations and nonlinear unmodeled dynamics ensuring asymptotic convergence of the tracking error to zero, and the boundedness of the adaptive gains. The nonlinear controller synthesis is given by a constructive method based on the solution of linear matrix inequalities. Besides, the simulation results show that, due to the nonlinearities, the rate of convergence of the proposed algorithm is faster than that provided by a classic MRAC.

Automated summary

This article presents a robust nonlinear model reference adaptive control (MRAC) method for disturbed linear systems, which can address parameter uncertainties, disturbances, and nonlinear unmodeled dynamics. Simulation results show that this method has a faster convergence rate compared to traditional MRAC.