Robust neural tracking control for switched nonaffine stochastic nonlinear systems with unknown control directions and backlash-like hysteresis

Shu, Yanjun; Tong, Yanhui; Chao-gang, YU

doi:10.1016/j.jfranklin.2019.12.011

Cited by 16 publications

(13 citation statements)

References 53 publications

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“…With the increase of the displacement of the column top, new cracks continue to appear in the front pull area of the upper and lower ends of the column, and the cracks have further expanded. At the same time, horizontal cracks also appeared on both sides of the upper and lower ends of the column [8]. When the displacement of the top of the column reaches 30 mm, the concrete at the upper and lower ends of the column will spall in a large area, and the angle steel and steel plate hoops will be exposed, and the angle steel will appear to be buckled under compression.…”

Section: Analysis Of Failure Form and Test Processmentioning

confidence: 99%

Composite mechanical performance of prefabricated concrete based on hysteresis curve equation

2021

Applied Mathematics and Nonlinear Sciences

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The angle steel-concrete column used in the new frame structure means that the rigid angle steel is placed in the column instead of the longitudinal reinforcement. The steel plate hoop welded to the longitudinal angle steel is used instead of the stirrup to form a spatial steel frame and concrete component. To ensure the normal use of existing houses in the building and adding floors, avoid transferring the load during the construction phase to the roof of the original house. The corresponding skeleton curve is extracted from the hysteresis curve of the specimen. Based on experimental research, the force performance of the normal section of the angle steel-concrete column was discussed, and the calculation formula of the normal section bearing capacity of the angle steel-concrete column was discussed.

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Section: Analysis Of Failure Form and Test Processmentioning

confidence: 99%

Composite mechanical performance of prefabricated concrete based on hysteresis curve equation

2021

Applied Mathematics and Nonlinear Sciences

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“…Event-triggered control, finite-time control, stochastic nonlinear systems, adaptive neural control, unknown time-varying control directions, input nonlinearities Control of stochastic nonlinear systems have attracted much attention in recent years. [1][2][3][4][5][6] Because many actual systems, such as robotic manipulators, 7 induction motors, 8 and so on, contain stochastic disturbances. Additionally, in actual implementations, the designed control strategy is expected to be finished in a finite time, such as the finite-time control method considered by [9][10][11] for deterministic nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, other studies of stochastic nonlinear systems with uncertain control directions may be encountered in. [32][33][34][35] It's worth noting that the unknown time-varying control directions for stochastic systems with finite-time stability have yet to be fully solved. This is one of the driving forces behind the work in this paper.…”

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confidence: 99%

Event-triggered adaptive neural finite-time tracking control for non-strict feedback stochastic nonlinear systems with unknown time-varying control directions and input nonlinearities

Yue

Zhang

Chen

2022

Journal of Low Frequency Noise, Vibration and Active Control

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This paper focuses on dynamic-surface-based event-triggered adaptive neural finite-time tracking control for a category of non-strict feedback stochastic nonlinear system subject to unknown time-varying control directions, and input nonlinearities. Firstly, an improved event-triggered mechanism is presented, which simultaneously considers tracking error variables and compensating for event errors in threshold value. Secondly, a novel Lemma is provided to address concurrently the issues of Nussbaum terms in stability analysis and stochastic system finite-time stability. Thirdly, neural networks are utilized to cope with unknown functions. In addition, the Nussbaum functions are applied to identify time-varying unknown control directions and input nonlinearities. Moreover, the errors of the dynamic surface technique are compensated successfully by error compensation signals. By combining the proposed Lemma 1 and event-triggered adaptive neural finite-time control scheme, finite-time stability of considered systems in probability can be guaranteed, the tracking error can drive to a small neighborhood of the origin in finite time, and the Zeno behavior can be excluded. Finally, the effectiveness of the designed control scheme has been demonstrated through a second-order numerical system and a mass-spring-damper example.

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“…Note that, in Xia and Zhang [30] and Song et al [31], the hysteresis nonlinearity is not considered. For the hysteresis nonlinear systems, recently, many DSC technique-based adaptive backstepping control schemes without constructing the hysteresis inverse have been reported in the literature [32][33][34]. For instance, in Yue et al [35], an adaptive fuzzy backstepping control scheme was proposed for a class of hysteresis nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

Adaptive fuzzy backstepping super‐twisting sliding mode control of nonlinear systems with unknown hysteresis

Wang

2021

Asian Journal of Control

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In this paper, an adaptive fuzzy backstepping super-twisting sliding mode control (AFBSTSMC) scheme is proposed for a class of nonlinear systems with unknown hysteresis, unmeasured states, and external disturbances. First, fuzzy logic systems are employed to approximate the unknown nonlinear functions of the controlled systems, and a fuzzy state observer is designed to estimate the unmeasured states. Then, combining the backstepping technique and adaptive sliding mode control with super-twisting algorithm, the AFBSTSMC scheme is proposed without constructing the hysteresis inverse. The problem of "explosion of complexity" inherent in the conventional backstepping design method is eliminated by utilizing the dynamic surface control technique. Moreover, the chattering phenomenon is significantly reduced by using the developed adaptive fuzzy super-twisting controller. It is proved that the proposed control scheme can guarantee that all the signals in the closed-loop system are semi-globally ultimately uniformly bounded and the observer and tracking errors can converge to a small domain of the origin. Finally, the effectiveness of the presented control scheme is confirmed in two examples including a numerical simulation and an inverted pendulum with unknown hysteresis actuator.

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Robust neural tracking control for switched nonaffine stochastic nonlinear systems with unknown control directions and backlash-like hysteresis

Cited by 16 publications

References 53 publications

Composite mechanical performance of prefabricated concrete based on hysteresis curve equation

Composite mechanical performance of prefabricated concrete based on hysteresis curve equation

Event-triggered adaptive neural finite-time tracking control for non-strict feedback stochastic nonlinear systems with unknown time-varying control directions and input nonlinearities

Adaptive fuzzy backstepping super‐twisting sliding mode control of nonlinear systems with unknown hysteresis

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