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2004•2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)Requires access

Adaptive state feedback control for a class of stochastic nonlinear systems

Huijin Fan, Shuzhi Sam Ge

Open publisher page 13 citations

Abstract

In this paper, tracking problem is studied for a class of stochastic nonlinear systems, which is in strict-feedback form and with unknown parametric nonlinearities. Under the condition of all system states being available for feedback, by employing the stochastic Lyapunov-like theorem and the backstepping design technique, an adaptive state feedback control is developed. The output of the closed-loop system is proven to follow the desired trajectory asymptotically in probability.

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What this paper is about

In this paper, tracking problem is studied for a class of stochastic nonlinear systems, which is in strict-feedback form and with unknown parametric nonlinearities. Under the condition of all system states being available for feedback, by employing the stochastic Lyapunov-like theorem and the backstepping design technique, an adaptive state feedback control is developed. The output of the closed-loop system is proven to follow the desired trajectory asymptotically in probability.

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OpenAlex reports 13 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In this paper, tracking problem is studied for a class of stochastic nonlinear systems, which is in strict-feedback form and with unknown parametric nonlinearities. Under the condition of all system states being available for feedback, by employing the stochastic Lyapunov-like theorem and the backstepping design technique, an adaptive state feedback control is developed. The output of the closed-loop system is proven to follow the desired trajectory asymptotically in probability.

Key concepts: Backstepping, Control theory (sociology), Strict-feedback form, Nonlinear system, Adaptive control, Trajectory, Parametric statistics, Lyapunov function

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