Conditioned Super-Twisting Algorithm for systems with saturated control action

Seeber, Richard; Reichhartinger, Markus

doi:10.1016/j.automatica.2020.108921

Cited by 44 publications

(38 citation statements)

References 26 publications

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“…The conditioning technique ameliorates the windup effect by constraining the magnitude of integral part of the controller. The superiority of the conditioned STA over other saturated STAs has already been shown in Seeber and Reichhartinger (2020), such as its fastest rising speed and smallest windup (overshoot) (Castillo et al, 2016;Golkani et al, 2018). The proposed algorithm in this paper takes advantage of the traits of the conditioned STA.…”

Section: Extension To Resisting Square-root Growth Disturbancesmentioning

confidence: 97%

“…Inspired by Seeber and Reichhartinger (2020), this note provides a modified STA with adaptive controller gains based on conditioning technique (Hanus et al, 1987), with which the transient performance of super-twisting controller is enhanced while the classical structure of STA is maintained. The stability proof for the new algorithm is simpler and more concise, and the stability proof methods that have already been rigorously studied for classical STA can be used directly.…”

Section: Control Structurementioning

confidence: 99%

“…In this section, the proposed adaptive conditioned STA (ACSTA) will be compared with the classical STA in (3), the New Modified STA (NMSTA) in (4) and the original conditioned STA in Seeber and Reichhartinger (2020) to demonstrate that the proposed ACSTA can indeed enhance the transient performance of the convergence process.…”

Section: Simulationmentioning

confidence: 99%

“…Based on the goal of Yang and Qin (2017), this paper proposes an adaptive STA based on conditioning technique, which is named the adaptive conditioned STA. Inspired by Seeber and Reichhartinger (2020), it can accelerate the convergence speed and reduce the overshoot simultaneously without changing the structure of the classical STA. The original conditioned STA is enhanced here and the controller gains are designed as adaptive.…”

Section: Introductionmentioning

confidence: 99%

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An adaptive super-twisting algorithm based on conditioning technique

Liu

Esche

Wang

2021

Transactions of the Institute of Measurement and Control

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This paper presents an adaptive conditioning-technique-based super-twisting algorithm aiming at improving the convergence speed and reducing the overshoot at the same time. Compared with a recently proposed method called new modified super-twisting algorithm, in which a linear acceleration factor and a damping factor are added to achieve this goal, the proposed method has several advantages. First, the proposed method enhances the convergence performance of the system by resorting to the characteristics of the conditioned super-twisting algorithm and the adaptive gains, without changing the basic structure of the classical super-twisting controller. Thus, stability proof of this method is much simpler and more concise. Furthermore, unlike the new modified super-twisting algorithm, in which an unnatural assumption on the Lipschitz disturbance is made for the stability proof, this method can counteract not only typical bounded Lipschitz disturbances but also square-root growth disturbances. Also, a set of less conservative control gains can be obtained with the proposed algorithm than with the compared algorithm. Apart from these benefits, several simulation results illustrate that the performance of the proposed method is even better in convergence and recovering from disturbance.

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Section: Extension To Resisting Square-root Growth Disturbancesmentioning

confidence: 97%

Section: Control Structurementioning

confidence: 99%

Section: Simulationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An adaptive super-twisting algorithm based on conditioning technique

Liu

Esche

Wang

2021

Transactions of the Institute of Measurement and Control

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“…For a first‐order system, a modification to the suboptimal second‐order sliding mode controller has been made by Ferrara and Rubagotti 4 in order to guarantee the finite‐time convergence of the sliding variable in the case of such a system with a saturating actuator. Several versions of the saturated supertwisting algorithm have been recorded in the literature, see, for example, the works done by Castillo et al, 5 Golkani et al, 6 and Seeber and Reichhartinger 7 . A domain of attraction for a system under the conventional supertwisting control has been computed by Behera et al 8 It is proved that in the case the initial condition of the closed‐loop system is within this domain, the control signal does not exceed the limits, that is, windup does not occur.…”

Section: Introductionmentioning

confidence: 99%

Lyapunov‐based saturated continuous twisting algorithm

Golkani

Seeber

Reichhartinger

et al. 2020

Intl J Robust & Nonlinear

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In this article, a second‐order system, which is affected by disturbances and uncertainties, with a saturating actuator is considered. A novel robust feedback control law is designed based on the sliding mode technique. The twisting and the continuous twisting algorithms are incorporated into the design, which is based on level curves of a Lyapunov function. The performance of the standard continuous twisting algorithm is greatly improved in the case that the initial condition of the system is far away from the origin. A parameter setting for the controller is given by establishing global finite‐time stability properties of the closed‐loop system origin. Feasibility and effectiveness of the proposed approach are indicated in a real‐world application as well as numerical simulation.

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Time‐varying sliding mode controller for over‐actuated systems with constrained and uncertain actuators in flight control applications

Tohidi

Yıldız

Kolmanovsky

2022

Intl J Robust & Nonlinear

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One solution to the problem of distributing the control action among redundant actuators with uncertain dynamics is employing an adaptive control allocator. This paper proposes a sliding mode controller which exploits a time‐varying sliding surface to complement adaptive control allocation in the presence of actuator saturation. The proposed approach does not require error augmentation for tracking desired references, which diminishes the computational burden. Aerodata Model in Research Environment, which is an over‐actuated aircraft model, is adopted to demonstrate the efficacy of the proposed controller in simulation studies.

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Conditioned Super-Twisting Algorithm for systems with saturated control action

Cited by 44 publications

References 26 publications

An adaptive super-twisting algorithm based on conditioning technique

An adaptive super-twisting algorithm based on conditioning technique

Lyapunov‐based saturated continuous twisting algorithm

Time‐varying sliding mode controller for over‐actuated systems with constrained and uncertain actuators in flight control applications

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