期刊:IEEE transactions on neural networks and learning systems [Institute of Electrical and Electronics Engineers] 日期:2021-11-08卷期号:34 (8): 5133-5143被引量:8
In this article, the problem of output feedback control for a class of stochastic nonlinear systems in the presence of nondifferentiable measurement function and input saturation is studied. A novel power-auxiliary system is introduced to handle the adverse effects of input saturation. What is more, the common growth assumptions of nonlinear terms can be eliminated by a key lemma. Then, an output feedback controller is constructed to ensure that all the signals in the closed-loop system are globally bounded almost surely. Finally, a simulation shows that the control strategy is effective.