Implementation of Super-Twisting Control on Higher Order Perturbed Integrator System using Higher Order Sliding Mode Observer

Kumari, Kiran; Chalanga, Asif; Bandyopadhyay, B.

doi:10.1016/j.ifacol.2016.10.276

Cited by 22 publications

(20 citation statements)

References 14 publications

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“…Using Euler parameters rather than Euler angles provides us the advantage of a well-defined Jacobian matrix, which is necessary to be able to use the inverse of the Jacobian matrix. However, at the same time, we cannot use the HOSMO from [22], which means that we need velocity measurements to control the system. The complete state vector specifying the position, orientation, and shape of the AIAUV is then represented as…”

Section: Modelling and The Tracking Control Problemmentioning

confidence: 99%

“…In [20] tracking control of the centre of mass of the AIAUV in 2D was considered by using STA with adaptive gains [19] and a higher-order sliding mode observer (HOSMO) [22]. It was proven that the tracking errors were ultimately bounded, and the simulation results demonstrated that the proposed control method provided excellent tracking capabilities.…”

Section: Introductionmentioning

confidence: 99%

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Tracking control of an articulated intervention AUV in 6DOF using the generalized super-twisting algorithm

Borlaug

Pettersen

Gravdahl

2019

2019 American Control Conference (ACC)

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The articulated intervention AUV (AIAUV) is an underwater swimming manipulator (USM) with intervention capabilities. Station-keeping and trajectory tracking are essential for the AIAUV to be able to move in confined spaces and to perform intervention tasks. In this paper we propose using the generalized super twisting algorithm, which is an extension of the regular super-twisting algorithm, for the trajectory tracking of the joint angles, position and orientation of the base of the AIAUV in 6DOF. Furthermore, we show the ultimate boundedness of the tracking errors. We also demonstrate the applicability of the proposed control law and compare the performance with the regular super-twisting algorithm with adaptive gains.

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Section: Modelling and The Tracking Control Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Tracking control of an articulated intervention AUV in 6DOF using the generalized super-twisting algorithm

Borlaug

Pettersen

Gravdahl

2019

2019 American Control Conference (ACC)

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“…By designing the observer structure as in , the state observer is chosen as follows:

\begin{matrix} right & left {\dot{\hat{p}}}_{1} = [\begin{matrix} {\overset{\overset{p}{true}}{true}}_{1, x} \\ {\overset{\overset{p}{true}}{true}}_{1, y} \end{matrix}] = [\begin{matrix} {\overset{p}{true}}_{2, x} + z_{1, x} \\ {\overset{p}{true}}_{2, y} + z_{1, y} \end{matrix}] & right \\ right & left {\dot{\hat{p}}}_{2} = [\begin{matrix} {\overset{\overset{p}{true}}{true}}_{2, x} \\ {\overset{\overset{p}{true}}{true}}_{2, y} \end{matrix}] = [\begin{matrix} {\overset{p}{true}}_{3, x} + z_{2, x} + \frac{1}{m_{t}} F_{normalC normalM, d_{x}} \\ {\overset{p}{true}}_{3, y} + z_{2, y} + \frac{1}{m_{t}} F_{normalC normalM, d_{y}} \end{matrix}] \\ right & left {\dot{\hat{p}}}_{3} = [\begin{matrix} {\overset{\overset{p}{true}}{true}}_{3, x} \\ {\overset{\overset{p}{true}}{true}}_{3, y} \end{matrix}] = [\begin{matrix} z_{3, x} \\ z_{3, y} \end{matrix}] \end{matrix}

…”

Section: Control and Observer Designmentioning

confidence: 99%

“…Since the STA is only applicable to systems where the control input appears in the equation for the first derivative of the sliding variable, both the position and velocity of the USM must be available for measurement. For the case when only the position measurements are available, we use a higher‐order sliding mode observer, as proposed in , to estimate the states. Hence, we combine the results from and , as done in , but we replace the regular STA with a STA with adaptive gains.…”

Section: Introductionmentioning

confidence: 99%

“…For the case when only the position measurements are available, we use a higher‐order sliding mode observer, as proposed in , to estimate the states. Hence, we combine the results from and , as done in , but we replace the regular STA with a STA with adaptive gains. Then, we apply this control structure to the USM and show the ultimate boundedness of the tracking errors.…”

Section: Introductionmentioning

confidence: 99%

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Trajectory Tracking for Underwater Swimming Manipulators using a Super Twisting Algorithm

Borlaug

Gravdahl

Sverdrup-Thygeson

et al. 2018

Asian Journal of Control

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The underwater swimming manipulator (USM) is a snake-like, multi-articulated, underwater robot that is equipped with thrusters. One of the main purposes of the USM is to act like an underwater floating base manipulator. As such, it is essential to achieve good station-keeping and trajectory tracking performance for the USM by using the thrusters and by using the joints to attain the desired position and orientation of the head and tail of the USM. In this 'paper, we propose a sliding mode control (SMC) law, specifically the super-twisting algorithm with adaptive gains, for the trajectory tracking of the USM's centre of mass. A higher-order sliding mode observer is proposed for state estimation. Furthermore, we show the ultimate boundedness of the tracking errors. We demonstrate the applicability of the proposed control law and show that it leads to better performance than a linear PD-controller.

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Real Implementation of an Active Fault Tolerant Control Based on Super Twisting Technique for a Robot Manipulator

Kang

2019

Intelligent Computing Methodologies

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Implementation of Super-Twisting Control on Higher Order Perturbed Integrator System using Higher Order Sliding Mode Observer

Cited by 22 publications

References 14 publications

Tracking control of an articulated intervention AUV in 6DOF using the generalized super-twisting algorithm

Tracking control of an articulated intervention AUV in 6DOF using the generalized super-twisting algorithm

Trajectory Tracking for Underwater Swimming Manipulators using a Super Twisting Algorithm

Real Implementation of an Active Fault Tolerant Control Based on Super Twisting Technique for a Robot Manipulator

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