Adaptive Backstepping Control of Uncertain Sandwich-Like Nonlinear Systems With Deadzone Nonlinearity

A systematic differentiator-based adaptive backstepping control methodology is proposed for a class of sandwich-like nonlinear system with unknown state-dependent deadzone nonlinearity and parametric uncertainties. The novelty of our approach is that a high-order sliding mode differentiator is utilized to estimate the nonstrict feedback coupling term resulting from the sandwiched deadzone, and all the outputs of the differentiator are integrated into the backstepping procedure based on Lyapunov functions with flat zone recursively. By this approach, all the unknown parameters are estimated online, the discontinuity of the virtual input caused by bound estimations is avoided. It is shown that the ultimate boundedness of all the closed-loop signals is achieved and the output tracking error converges to a preset set. Simulation is performed to verify the theoretical findings.

Automated summary

In this paper, a systematic differentiator-based adaptive backstepping control methodology is proposed for sandwich-like nonlinear systems. With the utilization of a high-order sliding mode differentiator, the nonstrict feedback coupling term resulting from the sandwiched deadzone is estimated and integrated into the backstepping procedure. Theoretical analysis and simulation experiments demonstrate that the proposed approach can achieve ultimate boundedness for closed-loop signals and convergence for output tracking error.