Parameter-dependent controller design of stochastic strict feedforward nonlinear systems

In this paper, the exponentially stable problem is discussed for a class of stochastic strict feedforward nonlinear systems. Firstly, by employing the proper coordinate transformation and the novel parameter-dependent controller, the initial stochastic strict feedforward nonlinear system is converted to an equivalent system. After that, the implementable parameter-dependent controller, which is adopted to handle the nonlinearities, can be achieved by reasonably selecting the designed parameter. Finally, by means of stochastic Lyapunov stability theory, it is rigorously verified that the proposed parameter-dependent state-feedback controller and parameter-dependent output-feedback controller can guarantee that the stochastic closed-loop system is the fourth moment exponentially stable. Simulation results demonstrate the efficiency of the proposed parameter-dependent controller. (C) 2021 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

Automated summary

This paper discusses exponentially stable problem for a class of stochastic strict feedforward nonlinear systems, presenting a parameter-dependent controller to handle nonlinearities. Through coordinate transformation and parameter selection, the proposed controller ensures stability of the closed-loop system as demonstrated by stochastic Lyapunov stability theory. Simulation results validate the efficiency of the proposed controller.