A new method of parameter estimation and adaptive control of nonlinear systems with filterless least-squares

This paper is concerned with the parameter estimation and adaptive control problem for a sort of strict-feedback nonlinear systems with unknown parameters. In order to deal with the nonlinear functions, we develop a kind of least-squares estimator in the parameter estimation part. With such an estimator, we design the state-feedback control law and analyze the properties of the closed-loop system. To be concrete, the parameter estimator can guarantee the boundedness of parameter estimate error. At the same time, the adaptive control law is proposed to make the system states converge to zero and the equilibrium stable globally under some common assumptions. Finally, simulations are given to demonstrate the theoretical results.