Finite-time backstepping control with command filter for a class of nonlinear systems with parametric uncertainties

Feng, Cong; Wang, Qing; Hu, Changhua; Zhang, Shen

doi:10.1177/0142331220909664

Cited by 13 publications

(13 citation statements)

References 35 publications

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“…Remark 2. Compared with previous work, 27,31,34 the main contributions of this research can be summarized as bellow.…”

Section: ) ▪mentioning

confidence: 98%

“…Recently, the interest in adaptive control of nonlinear systems is growing rapidly, and many promising schemes have been reported. [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37] There are a lot of remarkable results in the study of adaptive control schemes for nonlinear systems with quantized control signals, such as. [38][39][40][41][42][43][44][45][46][47][48] In Reference 38, the issue of finite-time tracking control was discussed for nonlinear quantized systems with unmeasurable states.…”

Section: Introductionmentioning

confidence: 99%

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Finite‐time adaptive fuzzy command filtering control for stochastic nonlinear systems with input quantization

Kang

Liu

Wang

2021

Adaptive Control & Signal

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This article focuses on the finite-time adaptive fuzzy control problem based on command filtering for stochastic nonlinear systems subject to input quantization. Fuzzy logic systems are employed to estimate unknown nonlinearities.In the control design, the hysteretic quantized input is decomposed into two bounded nonlinear functions, which solves the chattering problem. Meanwhile, an adaptive fuzzy controller is presented by the combination of command filter technique and backstepping control, which eliminates the computational complexity existing in traditional backstepping design. Under the proposed adaptive mechanism, all the closed-loop signals remain bounded while the desired system performance can be realized within finite time. The main significance of this work is that (1) the filtering error can be solved on the basis of the designed compensating signals;(2) the requirement of adaptive parameters is decreased to only one, which simplifies the controller design process and may improve the control performance. Two simulation examples are used to validity of the developed scheme.

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“…Remark 2. Compared with previous work, 27,31,34 the main contributions of this research can be summarized as bellow.…”

Section: ) ▪mentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Finite‐time adaptive fuzzy command filtering control for stochastic nonlinear systems with input quantization

Kang

Liu

Wang

2021

Adaptive Control & Signal

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“…In recent years, researchers have proposed some control methods for vehicle lateral stability. These control methods include robust control method (Liu and Dong, 2020), PID control method (Haroun and Li, 2020; Li et al, 2016; Zhang and Chi, 2020), sliding mode control method (Ding et al, 2017, 2018; Gu and Xu, 2020; Guo et al, 2020), finite-time control method (Feng et al, 2020; Sun et al, 2017a; Wang et al, 2020), and adaptive disturbance attenuation method (Sun and Wang, 2019; Sun et al, 2017b). However, these control methods are mainly studied in continuous-time.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear lateral motion stability control method for electric vehicle based on the combination of dual extended state observer and domination approach via sampled-data output feedback

Meng

Sun

2021

Transactions of the Institute of Measurement and Control

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This paper studies lateral motion stability control method for an electric vehicle (EV) with uncertain disturbances. Aiming to suppress the influence of uncertain disturbances, a novel method based on the combination of dual extended state observer (dESO) and domination approach is proposed. The proposed method enables the designed controller just to adopt a smaller scaling gain than the classic domination method, which is more practical for the controller in engineering. Firstly, a dESO is proposed to estimate the uncertain disturbances of the system. Also, a sampled-data output feedback domination approach is designed to dominate the disturbances by using a scaling gain. Then, the sampled-data output feedback control law is constructed based on the dESO and domination approach called dESOD. Furthermore, the stability analysis is presented to show that the proposed sampled-data controller can guarantee the closed-loop system globally asymptotically stable. Finally, the simulations and experiment results show the effectiveness of the proposed method.

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“…11–13 Recently, a command filter-based adaptive fuzzy controller has been proposed for a class of nonlinear systems with uncertain disturbance. 14 Feng et al 15 proposed a novel adaptive finite-time backstepping tracking control with command filter for a class of uncertain nonlinear systems. However, the time-delay, which plays an important role in control design, is not considered in the above research.…”

Section: Introductionmentioning

confidence: 99%

Command filtered adaptive neural tracking control of uncertain nonlinear time-delay systems with asymmetric time-varying full state constraints and actuator saturation

Fang

2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article investigates the command filtered adaptive neural tracking control for uncertain nonlinear time-delay systems subject to asymmetric time-varying full state constraints and actuator saturation. To stabilize such a class of systems, the radial basis function neural networks and the backstepping technique are used to structure an adaptive controller. The command filter is utilized to overcome the complexity explosion problem in backstepping. By employing the Lyapunov–Krasovskii functionals, the effect of time-delay is eliminated. The asymmetric time-varying barrier Lyapunov functions are designed to ensure full state constraint satisfaction. Moreover, the hyperbolic tangent function and an instrumental variable are introduced to deal with actuator saturation. All signals in the closed-loop system are proved to be bounded and the tracking error converges to a small neighborhood of the origin. Finally, two examples are provided to illustrate the effectiveness of the proposed method.

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Finite-time backstepping control with command filter for a class of nonlinear systems with parametric uncertainties

Cited by 13 publications

References 35 publications

Finite‐time adaptive fuzzy command filtering control for stochastic nonlinear systems with input quantization

Finite‐time adaptive fuzzy command filtering control for stochastic nonlinear systems with input quantization

Nonlinear lateral motion stability control method for electric vehicle based on the combination of dual extended state observer and domination approach via sampled-data output feedback

Command filtered adaptive neural tracking control of uncertain nonlinear time-delay systems with asymmetric time-varying full state constraints and actuator saturation

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