Lyapunov redesign for structural convergence improvement in adaptive control

The relative improvement of the convergence rate in adaptive error models is discussed. It is shown how to improve convergence, positive realness, and robustness by modifying the structure of the error model. The proposed approaches to designing adaptive control algorithms using the Lyapunov method not only improve the rate of convergence but also provide flexibility in choosing nonlinear control inputs. Boundedness of the nonlinear functions of the modified schemes is shown