Tracking controller design for random nonlinear benchmark system

Wu, Zhaojing; Wang, Shitong; Cui, Mingyue

doi:10.1016/j.jfranklin.2016.10.015

Cited by 36 publications

(16 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By the stability results in [12], [13] constructed an outputfeedback controller to achieve globally asymptotically stable in probability sense for stochastic high-order nonlinear timedelay systems satisfying some assumptions and [14] studied stabilization control for a class of stochastic upper-triangular nonlinear systems with time-delay by state feedback approach. However, for random nonlinear systems, most findings in existing literature (such as [7,[15][16][17][18][19]) didn't investigate the influence of time-delay phenomenon on systems dynamics behavior. The corresponding results about random nonlinear time-delay systems also have not been reported in existing literature.…”

Section: Introductionmentioning

confidence: 99%

Stability analysis of random nonlinear systems with time-varying delay and its application

2020

View full text Add to dashboard Cite

This paper studies a class of random nonlinear systems with time-varying delay, in which the r-order moment (r ≥ 1) of the random disturbance is finite. Firstly, some general conditions are proposed to guarantee the existence and uniqueness of the global solution to random nonlinear timedelay systems. Secondly, some definitions and criteria on noiseto-state stability in the moment sense and in probability sense are given by Lyapunov method respectively. Finally, two regulation controllers are constructed respectively for two corresponding random nonlinear time-delay systems and the effectiveness of two proposed recursive procedures are demonstrated by two simulation examples.

show abstract

Section: Introductionmentioning

confidence: 99%

Stability analysis of random nonlinear systems with time-varying delay and its application

2020

View full text Add to dashboard Cite

show abstract

“…In this paper we endeavor to explore the effect of those different uncertainties on stochastic systems performance analysis and controller design. Inspired by [28], [29] and [30], we address the state feedback stabilization problem for a class of stochastic nonlinear systems. The system is subject to three uncertainties including nonlinear parameter uncertainty, matched uncertainty and external disturbance.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Robust Control for a Class of Stochastic Nonlinear Uncertain Systems

Tian

Chen

2020

IEEE Access

View full text Add to dashboard Cite

This paper is concerned with the control design for a class of stochastic nonlinear systems. Three uncertainties are considered; that is, nonlinear parameter uncertainty, matched uncertainty and stochastic disturbance. The nonlinear uncertainty contains some uncertain parameter and satisfies bound condition. Neither the exact value of the matched uncertainty nor its possible bound is known; its upper bound function satisfies certain concave condition. The stochastic disturbance is a standard Wiener process. Based on stochastic Lyapunov stability theory, the adaptive robust controller is designed, which renders the state variables of the closed-loop system bounded in probability, regardless of all uncertainties. The desired controller is constructed by the upper bound function and the saturation function, in which the upper bound function represents the magnitude of the control, while the saturation function indicates the control direction. The design of the adaptive robust controller is based on the minimum information of uncertainty, which is simple and can be easily realized in practical systems. Finally, a two-tank water level control example is used to demonstrate the effectiveness of our control design. INDEX TERMS Stochastic system, nonlinear system, uncertainty, adaptive control, bounded in probability.

show abstract

“…9,[17][18][19] Following the line of Wu, 16 a series of results about the stabilization and tracking of random nonlinear systems is obtained. [20][21][22][23] The above discussions motivate us to focus on random Markovian switching systems. Compared with stochastic Markovian switching systems, the results of random Markovian switching systems are few, and the existing results are mostly based on random strict-feedback nonlinear systems, such as in the work of Jiao et al 24 Jiao et al 24 gave the definitions of noise-to-state stability for a class of random strict-feedback Markovian switching systems in the probability sense and in the moment sense.…”

Section: Introductionmentioning

confidence: 99%

Adaptive tracking control for a class of random pure‐feedback nonlinear systems with Markovian switching

Yao

Zhang

2018

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

This note studies the tracking control problem for a class of random pure-feedback nonlinear systems with Markovian switching and unknown parameters. An adaptive tracking controller is constructed by introducing an auxiliary integrator subsystem and using the improved backstepping method such that the closed-loop system has a unique solution that is globally bounded in probability. Meanwhile, the tracking error can converge to an arbitrarily small neighborhood of zero via the parameter regulation technique. The efficiency of the tracking controller designed in this paper is demonstrated by simulation examples. KEYWORDSbackstepping, Markovian switching, random pure-feedback systems, tracking control 3112

show abstract

Tracking controller design for random nonlinear benchmark system

Cited by 36 publications

References 10 publications

Stability analysis of random nonlinear systems with time-varying delay and its application

Stability analysis of random nonlinear systems with time-varying delay and its application

Adaptive Robust Control for a Class of Stochastic Nonlinear Uncertain Systems

Adaptive tracking control for a class of random pure‐feedback nonlinear systems with Markovian switching

Contact Info

Product

Resources

About