Global finite‐time output stabilization of nonlinear systems with unknown measurement sensitivity

Abstract

SummaryThis paper focuses on the output stabilization problem for a class of strict‐feedback systems with unknown nonlinear dynamics and unknown measurement sensitivity. The imprecise sensor measurements render the existing robust control approaches such as neuro or fuzzy control infeasible. A solution is provided in this paper by a feat of the concept of tuning functions and barrier Lyapunov functions (BLFs). Utilizing the modification capability of tuning functions, global stability is preserved. Exploiting the potential robustness of BLFs, the effect of unmodeled dynamics is counteracted under sensitivity errors. The combination of tuning functions with BLFs further leads to a distinct property that the real system output converges to an adjustable region in finite time. Compared with the existing results, the need for prior knowledge of system nonlinearities and measurement sensitivity is removed in this paper. Finally, simulation results illustrate the established theoretical findings.