Barrier Function-Based Adaptive Super-Twisting Controller

Obeid, Hussein; Laghrouche, Salah; Fridman, Leonid; Chitour, Yacine; Harmouche, Mohamed

doi:10.1109/tac.2020.2974390

Cited by 76 publications

(48 citation statements)

References 19 publications

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“…Now, consider the case η(t) < η 1 ,V 2 will be sign indefinite and η(t) may leave for η 1 . Similar to the treatment in [25][26][27], [35],V 2 ≤ 0 and V 2 will be constant or decreasing again once η(t) reaches η 1 , which means that |η(t)| ≤ η 1 holds for the rest of time.…”

Section: Stability Analysismentioning

confidence: 85%

Saturated adaptive barrier sliding mode control with state‐dependent uncertainty limit

Liu

et al. 2021

IET Control Theory & Appl

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This paper proposed a saturated adaptive barrier sliding mode control (SABSMC) for disturbed systems with parameter uncertainty, external disturbance, and input saturation. One distinctive feature of the proposed method is that even under the influence of input saturation, it is able to drive the system trajectory into a prespecified neighbourhood of the sliding surface, independent of the upper limit of lumped disturbance. Moreover, attributing to the designed adaptive laws, the switching gain of the proposed method can be adaptively adjusted in a wise manner. Another attractive feature of the proposed method is that it removes any presumption of constant upper limit on the lumped disturbance. Instead, SABSMC utilises a more rational state-dependent upper limit assumption. The system dynamics of the closed-loop system is analysed via the Lyapunov method in the presence of parameter uncertainty, external disturbance, and input saturation. The effectiveness of the proposed method is confirmed through numerical simulations.

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Section: Stability Analysismentioning

confidence: 85%

Saturated adaptive barrier sliding mode control with state‐dependent uncertainty limit

Liu

et al. 2021

IET Control Theory & Appl

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“…The closed-loop stability-based Lyapunov, the problem of robustness against uncertainties and convergence time estimation issues have been widely discussed in the literature (Moreno, 2009;Moreno and Osorio, 2012;Castillo et al, 2018). Otherwise, several works attempted to enhance this algorithm, such as adaptive super-twisting control (Plestan and Chriette, 2012;Borlaug et al, 2020;Obeid et al, 2020), variable gains super-twisting (Dávila et al, 2010;Gonzalez et al, 2012;Vidal et al, 2017) and TDE-based optimal super-twisting (Kali et al, 2018b;Wang Y. et al, 2018). This latter is easy to implement and gives good results on a redundant robot arm.…”

Section: Discrete-time Super-twisting Algorithm Controlmentioning

confidence: 99%

Recent Advances in Model Predictive and Sliding Mode Current Control Techniques of Multiphase Induction Machines

et al. 2021

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Multiphase machines have attracted the attention of the research and industrial communities due to their advantages, namely better power distribution and fault-tolerant capabilities without extra hardware. However, the multiphase machine requires high-performance control strategies to take advantage of these features. From this perspective, the field-oriented control with the inner current control loop that uses using an explicit modulation stage has been considered the benchmark solution thanks to the reduced harmonic distortion obtained with this regulation strategy. Nevertheless, nonlinear controllers, thanks to their inherent nature, allow exploiting the extra multiphase capabilities in a simplified manner. Consequently, this paper aims to concentrate and discuss the latest developments on nonlinear current control of two of the most popular multiphase electric drive configurations, five-phase and six-phase. Then, this paper covers mainly finite-control-set model predictive control and their variations. Moreover, sliding-mode control is also explained. Finally, this paper includes experimental assessments of the most recent nonlinear current control techniques considering steady-state and transient conditions, stability and performance analysis.

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“…Thus, in this paper, adaptive control gains are presented based on the barrier function. Characteristics of the barrier function can be obtained from [42]. Here, the barrier function is chosen as:…”

Section: Control Designmentioning

confidence: 99%

Variable-Gain Higher-Order Sliding Mode Pitch Control of Floating Offshore Wind Turbine

Han

Pan

et al. 2021

JMSE

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A variable-gain higher-order sliding mode pitch control strategy is proposed for a strongly nonlinear and coupled floating offshore wind power system. The main goal of the proposed strategy is to suppress platform motion caused by random disturbances such as waves and wind speed and to reduce fatigue loads and power fluctuations. Feedback control and super-twisting second-order sliding mode algorithm were adopted to carry out collective pitch control and track the rated rotor speed, which involves the factor of platform pitch. To adaptively adjust the collective pitch control parameters according to random wave and wind speed disturbances, the barrier function method was used to conceive adaptive sliding mode control gains. For comparison purposes, the proposed control strategy and PI control were executed under different wind and wave conditions on a FAST and MATLAB/Simulink platform. Furthermore, the fatigue load was calculated by Mlife. The results demonstrate that the proposed scheme is effective and robust. Moreover, it has advantages in resisting external disturbances, especially in suppressing the platform pitch and roll, as well as reducing the power fluctuations and the fatigue load on the blade root.

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Barrier Function-Based Adaptive Super-Twisting Controller

Cited by 76 publications

References 19 publications

Saturated adaptive barrier sliding mode control with state‐dependent uncertainty limit

Saturated adaptive barrier sliding mode control with state‐dependent uncertainty limit

Recent Advances in Model Predictive and Sliding Mode Current Control Techniques of Multiphase Induction Machines

Variable-Gain Higher-Order Sliding Mode Pitch Control of Floating Offshore Wind Turbine

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