Neural network-based adaptive output feedback fault-tolerant control for nonlinear systems with prescribed performance

Wang, Cai-Cheng; Yang, Guang‐Hong

doi:10.1016/j.neucom.2018.11.006

Cited by 41 publications

(16 citation statements)

References 38 publications

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“…

sat (\cdot)

represents the asymmetric saturation function described as

sat (v) = \{\begin{array}{ll} \overset{v}{true}, & if v \geq \overset{v}{true}, \\ v, & if \underline{v} < v < \overset{v}{true}, \\ \underline{v}, & if v \leq \underline{v}, \end{array}

where

\underline{v}

and

\overset{true‾}{v}

are two constants indicating the asymmetric saturation bounds. To facilitate control design, an approximation utilized in Reference 16 to the saturation function

sat (\cdot)

is employed that is expressed as

sat (v) = s (v) + ϵ (v),

where

ϵ (v) = sat (v) - s (v)

is bounded and an unknown constant

\overset{true‾}{ϵ}

can be found, satisfying

| ϵ | \leq \overset{true‾}{ϵ}

s (v)

is described by the Gauss error function

erf (\cdot)

…”

Section: Problem Formulationmentioning

confidence: 99%

“…The mentioned singularity problem was avoided via introducing an auxiliary system and an auxiliary variable in Reference 1. An approximation of the original input saturation can be tactfully realized by means of a smoothly differentiable hyperbolic tangent function 11‐15 or the Gauss error function 16 . However, the inputs in References 11, 12, and 14 were bounded by some known and symmetric boundaries.…”

Section: Introductionmentioning

confidence: 99%

“…To tackle the unknown and asymmetric input constraints, some intelligent or optimal control algorithms are usefully applied to some ordinary differential equation dominated systems. A Nussbaum gain technique was combined with neural network approximation to compensate the asymmetric input saturation of a nonlinear system 16 . In Reference 19, an optimal control framework was proposed to address a persistent monitoring problem using second‐order agents, where the movement of each agent was controlled via its acceleration and the acceleration input was bounded by asymmetric bounds.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Stabilization control of a flexible marine riser with failed and bounded actuator and time‐varying boundary constraints

Han

Liu

2021

Intl J Robust & Nonlinear

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In this article, we investigate the stabilization control problem of a flexible marine riser system with a failed and bounded control action and time‐varying boundary constraints. The considered system is modeled as a distributed parameter system dominated by a partial differential equation. The involved problems are extended to some more general conditions. The saturation and failures of the actuator make the input and output of the actuator a nonlinear relationship, which leads to the normally designed control input invalid. By applying the Nussbaum gain technique, we report a synthetical control method to tackle the input nonlinearity. A piecewise barrier Lyapunov function (BLF) is introduced to reduce the boundary displacement in an asymmetric open set. Compared with the traditional BLFs, the initial boundary displacement is not forced to retain within the given region by integrating a shifting function into the BLF design. In addition, the adaptive method is combined with the hyperbolic tangent function to provide a smooth control solution to the unknown parameters from nonlinear input and external perturbation. Relying on a Lyapunov‐based analysis and a numerical simulation, it is proven that the actuated riser system is uniformly bounded and the boundary displacement always keeps in the limited set even subject to actuator failures and limitations.

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“…

sat (\cdot)

represents the asymmetric saturation function described as

sat (v) = \{\begin{array}{ll} \overset{v}{true}, & if v \geq \overset{v}{true}, \\ v, & if \underline{v} < v < \overset{v}{true}, \\ \underline{v}, & if v \leq \underline{v}, \end{array}

where

\underline{v}

and

\overset{true‾}{v}

are two constants indicating the asymmetric saturation bounds. To facilitate control design, an approximation utilized in Reference 16 to the saturation function

sat (\cdot)

is employed that is expressed as

sat (v) = s (v) + ϵ (v),

where

ϵ (v) = sat (v) - s (v)

is bounded and an unknown constant

\overset{true‾}{ϵ}

can be found, satisfying

| ϵ | \leq \overset{true‾}{ϵ}

s (v)

is described by the Gauss error function

erf (\cdot)

…”

Section: Problem Formulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Stabilization control of a flexible marine riser with failed and bounded actuator and time‐varying boundary constraints

Han

Liu

2021

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

show abstract

“…Owing to the mean value theorem [42], f i (x i ) could be defined as f i (x i ) =z 1fi (x i ), withz 1 =y to be defined later. Hence, the term…”

Section: (A) Construction Of Nonlinear Observermentioning

confidence: 99%

“…Owing to the mean value theorem [42], fifalse(x¯ifalse) could be defined as fifalse(x¯ifalse)=z˘1f˘ifalse(x¯ifalse), with z˘1=y˘ to be defined later. Hence, the term w0||Q|false|2∑i=1nfi2false(x¯ifalse) in (3.7) is given by w0||Q|false|2∑i=1nfi2false(x¯ifalse)=z˘1w0||Q|false|2∑i=1n…”

Section: Control Designmentioning

confidence: 99%

Adaptive neural network control for nonlinear cyber-physical systems subject to false data injection attacks with prescribed performance

Liu

Tang

Zhao

et al. 2021

Phil. Trans. R. Soc. A.

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Cyber-physical systems (CPSs), as emerging products of industry 4.0 , play a key role in the development of intelligent manufacturing. This paper proposes an observer-based adaptive neural network (NN) control for nonlinear strict-feedback CPSs subject to false data injection attacks. Since there may be strict constraints on the state or output signals of nonlinear cyber-physical systems (NCPSs), we propose a time-varying asymmetric barrier Lyapunov function to realize the specific output constraints of NCPSs under cyber-attacks. Besides, since false data injection attacks will corrupt the transmitted state variables, an observer is designed to obtain observations of the exact states, and NN is used to approximate the unknown nonlinearity of NCPSs. With the proposed control strategy, the constraint control problem of NCPSs subject to false data injection attacks is settled. Finally, a numerical simulation example verifies the effectiveness of the proposed controller. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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Vibration suppression and fault‐tolerant control of an aerial refueling hose with multiple actuators

Song

Yan

Wang

et al. 2022

Asian Journal of Control

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In this paper, we propose an adaptive fault‐tolerant boundary vibration control approach for the flexible aerial refueling hose with variable length, variable speed, and multiple actuators. A distributed parameter system (DPS) is utilized to represent the dynamic behavior of the flexible refueling hose more precisely and accurately. Based on the established DPS model, we present a boundary vibration controller to suppress the vibration of the flexible refueling hose. In the controller, fault‐tolerant control with multiple actuators is considered to tackle the failure issues, and both multiplicative and additive failures are discussed in the fault situation. Then, by the Lyapunov direct method, we prove that the stability of the closed‐loop system is guaranteed under the proposed control approach. Numerical examples are presented to support the theoretical derivation.

show abstract

Neural network-based adaptive output feedback fault-tolerant control for nonlinear systems with prescribed performance

Cited by 41 publications

References 38 publications

Stabilization control of a flexible marine riser with failed and bounded actuator and time‐varying boundary constraints

Stabilization control of a flexible marine riser with failed and bounded actuator and time‐varying boundary constraints

Adaptive neural network control for nonlinear cyber-physical systems subject to false data injection attacks with prescribed performance

Vibration suppression and fault‐tolerant control of an aerial refueling hose with multiple actuators

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