Adaptive observer-based control for uncertain nonlinear stochastic systems with time-delay

2016 ◽  
Vol 353 (14) ◽  
pp. 3595-3609 ◽  
Author(s):  
Xiufeng Miao ◽  
Longsuo Li
Keyword(s):  
Time Delay ◽  
Stochastic Systems ◽  
Adaptive Observer ◽  
Nonlinear Stochastic Systems

scholarly journals Asymptotic Stability of Delay-Controlled Nonlinear Stochastic Systems with Actuator Failures

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
N. Zhou ◽  
R. H. Huan
Keyword(s):  
Time Delay ◽  
Asymptotic Stability ◽  
Stochastic Systems ◽  
Sufficient Conditions ◽  
Original System ◽  
Stochastic Averaging ◽  
Largest Lyapunov Exponent ◽  
Control Force ◽  
Nonlinear Stochastic Systems ◽  
Actuator Failures

The problem of asymptotic stability of delay-controlled nonlinear stochastic systems with actuator failures is investigated in this paper. Such a system is formulated as a continuous-discrete hybrid system based on the random switch model of failure-prone actuator. Time delay control force is converted into delay-free one by randomly periodic characteristic of the system. Using limit theorem and stochastic averaging, an approximate formula for the largest Lyapunov exponent of the original system is then derived, from which necessary and sufficient conditions for asymptotic stability are obtained. The validity and utility of the proposed procedure are demonstrated by using a stochastically driven nonlinear two-degree system with time delay feedback and actuator failure.

scholarly journals H∞Control for Nonlinear Stochastic Systems with Time-Delay and Multiplicative Noise

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Ming Gao ◽  
Weihai Zhang ◽  
Zhengmao Zhu
Keyword(s):  
Time Delay ◽  
General Class ◽  
Multiplicative Noise ◽  
Stochastic Systems ◽  
Design Method ◽  
Infinite Horizon ◽  
Control Design ◽  
Mean Square ◽  
Nonlinear Stochastic Systems ◽  
Numerical Examples

This paper studies the infinite horizonH∞control problem for a general class of nonlinear stochastic systems with time-delay and multiplicative noise. The exponential/asymptotic mean squareH∞control design of delayed nonlinear stochastic systems is presented by solving Hamilton-Jacobi inequalities. Two numerical examples are provided to show the effectiveness of the proposed design method.

A Variational Method for Approximating the Response of Nonlinear Stochastic Systems

1974 ◽  
Vol 96 (3) ◽  
pp. 353-357
Author(s):  
L. D. Zirkle ◽  
L. G. Clark
Keyword(s):  
Approximate Solution ◽  
Time Delay ◽  
Nonlinear Systems ◽  
Variational Method ◽  
Variational Methods ◽  
Stochastic Systems ◽  
Random Variables ◽  
Nonlinear Stochastic Systems ◽  
Non Gaussian

A method is introduced for determining approximate properties of the response of nonlinear stochastic systems. The method is based in concept on the variational methods of mechanics and allows the consideration of classes of systems not readily subject to analysis by existing techniques. Three examples are presented illustrating the application to nonlinear systems with non-stationary inputs, non-Gaussian inputs and with time delay. The main limitation of the technique is the necessity for assuming a meaningful form for the approximate solution in terms of arbitrary random variables.

Adaptive multi-dimensional Taylor network control for nonlinear stochastic systems with time-delay

2021 ◽  
pp. 095965182110402
Author(s):  
Shan-Liang Zhu ◽  
Ming-Xin Wang ◽  
Yu-Qun Han
Keyword(s):  
Time Delay ◽  
Stochastic Systems ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Network Control ◽  
Closed Loop System ◽  
Integral Type ◽  
Nonlinear Stochastic Systems ◽  
Network Controller ◽  
Control Scheme

In this article, the problem of adaptive multi-dimensional Taylor network control for strict-feedback nonlinear stochastic systems with time-delay is investigated. To overcome the control degradation resulting from the delay terms, the appropriate integral-type Lyapunov–Krasovskii functions are introduced. A novel adaptive multi-dimensional Taylor network control scheme is provided via backstepping technique. The proposed adaptive multi-dimensional Taylor network controller can ensure that all signals in the closed-loop system are bounded in probability and the tracking error eventually converges to a small neighborhood of the origin. Three simulation examples are given to demonstrate the effectiveness of the proposed control scheme.

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