Tracking control for switched nonlinear systems subject to output hysteresis via adaptive multi-dimensional Taylor network approach

He, Wenjing; Zhu, Shuqian; Li, Na; Han, Yu‐Qun

doi:10.1080/00207179.2022.2067787

Cited by 7 publications

(4 citation statements)

References 47 publications

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“…Assumption 2 (39). For ∀k ∈ M, i = 1, 2, … , N and j = 1, 2, … , n i , the time-varying disturbance Δ i,j,k ( t, 𝝓 i,j…”

Section: System Descriptionmentioning

confidence: 99%

“…(i) On the basis of backstepping technology, the construction of Lyapunov functions and the controller design process are procedural, which ensures that the control strategy proposed in this article is easy to achieve. (ii) Either in comparison to large‐scale nonlinear systems 27,28 or switched nonlinear systems 29 with asymmetric input saturation constraints, or in comparison to switched nonlinear systems with output hysteresis, 39 this article investigates the control problem of more general large‐scale switched nonlinear systems, and the proposed controller structures are simpler. (iii) As a kind of NN with special structure, MTN adopts polynomial to approximate nonlinearity, which greatly reduces the computational complexity.…”

Section: Simulation Studymentioning

confidence: 99%

“…34 Compared with the above models, the modified Bouc-Wen hysteresis model was put forward by, 35 which can preferably solve the more general hysteresis problem. Based on the modified Bouc-Wen hysteresis model, for switched systems or large-scale systems, many interesting research results about unknown hysteresis have been obtained, such as input hysteresis, 36,37 backlash-like hysteresis, 38 output hysteresis 39,40 . However, according to our current knowledge, there is no research on large-scale switched nonlinear systems with output hysteresis.…”

Section: Introductionmentioning

confidence: 99%

“…The control strategy proposed in Reference 36 is only suitable for controlling large‐scale systems with unknown actuator hysteresis, rather than switched systems with output hysteresis. Even though the control results of switched systems with output hysteresis were reported in References 39 and 40, the controlled objects do not include large‐scale systems. The authors of References 23 and 24 considered the tracking control problem of large‐scale switched systems, but the problem of output hysteresis cannot be solved. It seems to us that little has been known about the research of large‐scale systems, switched systems, asymmetric input saturation, output hysteresis and MTN technology appearing in the same framework.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach

Han

et al. 2022

Intl J Robust & Nonlinear

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For large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis, an adaptive control strategy is put forward by using a novel neural network, that is, multi‐dimensional Taylor network (MTN), which can effectively cope with the output tracking problem of this system. Firstly, asymmetric input saturation is expressed as the combination of a linear function and a bounded error function. Then, the modified Bouc‐Wen hysteresis model is employed to solve the nonlinear problem caused by output hysteresis. Afterwards, based on the approximation ability of MTN, a novel adaptive decentralized control method is designed by combining Lyapunov stability theory with adaptive backstepping technology, which realizes the stability and boundedness of the controlled systems. It should be noted that the asymmetric input saturation, the output hysteresis, large‐scale nonlinear systems and switched nonlinear systems appear in the same framework for the first time. Finally, a practical example and a numerical example are given to verify the availability of the proposed control strategy.

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“…Assumption 2 (39). For ∀k ∈ M, i = 1, 2, … , N and j = 1, 2, … , n i , the time-varying disturbance Δ i,j,k ( t, 𝝓 i,j…”

Section: System Descriptionmentioning

confidence: 99%

Section: Simulation Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach

Han

et al. 2022

Intl J Robust & Nonlinear

Self Cite

View full text Add to dashboard Cite

show abstract

Adaptive finite‐time tracking control of nonlinear systems subject to input hysteresis and multiple objective constraints

Zhao,

Han,

Zhou

et al. 2024

Intl J Robust & Nonlinear

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In this article, the problem of adaptive finite‐time tracking control for a class of nonlinear systems subject to backlash‐like input hysteresis and multiple objective constraints is investigated. For the purpose of realizing multiple objective constraints, a new time‐varying barrier function (TVBF) is introduced to ensure that all objective constraint functions are always within the defined range. Meanwhile, based on the combination of the command filter approach and adaptive backstepping control, an error compensation system (ECS) is supplied to reduce the impact of filter error on control performance. Additionally, the problem of “singularity” caused by hysteresis is avoided by linearizing the backlash‐like hysteresis model, and Nussbaum‐type function is also applied to reduce the influence of hysteresis on the stability of the system. Then, by combining multi‐dimensional Taylor network (MTN) technology and command filter backstepping approach, an adaptive finite‐time control strategy is designed. The proposed control strategy ensures that all the signals in the closed‐loop system realize finite‐time semi‐globally uniformly ultimately bounded (SGUUB), and the output signal of the system can track the reference signal greatly while adhering to multiple objective constraints. Finally, the effectiveness of the proposed control strategy is verified by a practical simulation example.

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Adaptive Decentralized Tracking Control for a Class of Large-Scale Nonlinear Systems with Dynamic Uncertainties Using Multi-dimensional Taylor Network Approach

Shan

Han

et al. 2022

Neural Process Lett

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Tracking control for switched nonlinear systems subject to output hysteresis via adaptive multi-dimensional Taylor network approach

Cited by 7 publications

References 47 publications

Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach

Tracking control for large‐scale switched nonlinear systems subject to asymmetric input saturation and output hysteresis: A new adaptive network‐based approach

Adaptive finite‐time tracking control of nonlinear systems subject to input hysteresis and multiple objective constraints

Adaptive Decentralized Tracking Control for a Class of Large-Scale Nonlinear Systems with Dynamic Uncertainties Using Multi-dimensional Taylor Network Approach

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