The generalized super-twisting algorithm with adaptive gains

Borlaug, Ida-Louise Garmann; Pettersen, Kristin Y.; Gravdahl, Jan Tommy

doi:10.23919/ecc51009.2020.9143617

Cited by 12 publications

(4 citation statements)

References 27 publications

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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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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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“…For comparison, three extra control schemes are briefly introduced here, including PD controller, super-twisting sliding mode controller (STSMC) and adaptive super-twisting sliding mode controller (ASTSMC). The adaptive law used in ASTSMC is commonly seen in several researches, namely [ 16 , 17 , 18 ].…”

Section: Simulationsmentioning

confidence: 99%

“…Replacing the signum function with other smooth functions may contribute to chattering attenuation but degrade the robustness to some extent. Moreover, some recent researches are focused on the adaptive methods to improve the sliding mode controller or observer [ 16 , 17 , 18 ]. The introduction of adaptive methods can certainly improve the performance of the original super-twisting algorithm.…”

Section: Introductionmentioning

confidence: 99%

Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Kang

Rong

Chou

2020

Sensors

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In this paper, an output-feedback fuzzy adaptive dynamic surface controller (FADSC) based on fuzzy adaptive extended state observer (FAESO) is proposed for autonomous underwater vehicle (AUV) systems in the presence of external disturbances, parameter uncertainties, measurement noises and actuator faults. The fuzzy logic system is incorporated into both the observers and controllers to improve the adaptability of the entire system. The dynamics of the AUV system is established first, considering the external disturbances and parameter uncertainties. Based on the dynamic models, the ESO, combined with a fuzzy logic system tuning the observer bandwidth, is developed to not only adaptively estimate both system states and the lumped disturbances for the controller, but also reduce the impact of measurement noises. Then, the DSC, together with fuzzy logic system tuning the time constant of the low-pass filter, is designed using estimations from the FAESO for the AUV system. The asymptotic stability of the entire system is analyzed through Lyapunov’s direct method in the time domain. Comparative simulations are implemented to verify the effectiveness and advantages of the proposed method compared with other observers and controllers considering external disturbances, parameter uncertainties and measurement noises and even the actuator faults that are not considered in the design process. The results show that the proposed method outperforms others in terms of tracking accuracy, robustness and energy consumption.

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“…There are not requirements about the upper-bound of the disturbance and its derivative. In Borlaug et al (2020), it is developed an adaptive generalised ST algorithm for a class of systems whose disturbances and uncertain control coefficients are time- and state-dependent. This approach uses dynamically adapted control gains that ensure global finite time convergence.…”

Section: Introductionmentioning

confidence: 99%

Exponential sliding mode controller for tracking trajectory of nonlinear systems

Hernandez-Gonzalez,

Alanis,

Rios

et al. 2023

Transactions of the Institute of Measurement and Control

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This paper proposes a control algorithm based on the sliding mode (SM) control law with an exponential term which improves the convergence to the origin. Such convergence to the origin is compared with other existing results such as the super-twisting (ST) and an SM controller with exponential terms. To compensate for unknown but bounded disturbances, a discontinuous function through an integral action has been employed. The presented algorithm with the exponential term, or exponential SM control algorithm, has been employed to a nonlinear system that can be represented into a block controllable form to follow an admissible trajectory. Finally, a real-time experiment and a numerical simulation have been carried out on a direct current motor to show effectiveness of the proposed control law. Numerical simulations have been compared with the ST control law and with a predefined-time controller with expon0ential terms.

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The generalized super-twisting algorithm with adaptive gains

Cited by 12 publications

References 27 publications

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

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

Antidisturbance Control for AUV Trajectory Tracking Based on Fuzzy Adaptive Extended State Observer

Exponential sliding mode controller for tracking trajectory of nonlinear systems

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