Hybrid position–admittance realization of an adaptive output super-twisting controller for a robotic scalpel

Sanchez-Magos, M.; Lazaro, Rafael Perez San; Mireles, Caridad; Ballesteros, Mariana; Salgado, Iván; Chairez, Isaac

doi:10.1016/j.conengprac.2019.104161

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…At present, the most effective method to weaken the chattering problem is the super-twisting algorithm (STA) in high-order sliding mode control, which can produce continuous control signals and has attracted the attention of many scholars. [16][17][18][19] However, STA can only be used for systems with relative order 1, which limits its application to some extent.…”

Section: Introductionmentioning

confidence: 99%

“…The main contributions of this paper are as follows: (1) Compared with references, [11][12][13][14][15] the proposed control law is continuous without discontinuous high-frequency switching term, which effectively weakens the chattering and ensuring the robustness of the system. And compared with references [16][17][18][19] , the control method is not affected by the relative order of the system, which can greatly improve the practicability of the method. (2) The proposed method gets rid of the dependence on the system model.…”

Section: Introductionmentioning

confidence: 99%

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Radial basis function neural network based second-order sliding mode control for robotic manipulator

Chen

Tang

Zhao

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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An adaptive second-order sliding mode control method based on RBF neural network is proposed for n-DOF robotic manipulators in the presence of external disturbances. First, RBF neural network is used to approximate the model information. Second, by using adaptive technology to compensate the uncertainty, whose prior knowledge about upper bound is not required. In addition, since the proposed control scheme is continuous, the chattering phenomenon is almost completely eliminated. Finally, the stability and finite time convergence of the proposed method are proved by Lyapunov stability theory. Through the simulation of 2-DOF manipulator and 5-DOF manipulator, the effectiveness and superiority of the control scheme are verified.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Radial basis function neural network based second-order sliding mode control for robotic manipulator

Chen

Tang

Zhao

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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show abstract

“…SMC is a nonlinear control method that has proven an effective robust control for modifying the dynamics of nonlinear systems by application of a discontinuous control signal according to [30]. This robust control methodology has been applied to a wide variety of practical systems, such as general industrial applications, e.g., electric power systems including permanent magnet synchronous motors which are favorable in transportation [31], electromechanical [32] and electro-hydraulic systems [33], and robotics including multitude of medical usages like robotic scalpel position control [34] or control for lower limb rehabilitation as well [35]. Furthermore, aerospace controls are also involved, like space manipulators [36], thrust-vector control for spacecraft landing [37] active suppression for combustion instabilities [38], or limit protection control for gas turbine engines [39] as well as setpoint tracking control with output constraints for turbofans [40].…”

Section: Introductionmentioning

confidence: 99%

Sliding Mode Control for Micro Turbojet Engine Using Turbofan Power Ratio as Control Law

Derbel

Beneda

2020

Energies

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The interest in turbojet engines was emerging in the past years due to their simplicity. The purpose of this article is to investigate sliding mode control (SMC) for a micro turbojet engine based on an unconventional compound thermodynamic parameter called Turbofan Power Ratio (TPR) and prove its advantage over traditional linear methods and thrust parameters. Based on previous research by the authors, TPR can be applied to single stream turbojet engines as it varies proportionally to thrust, thus it is suitable as control law. The turbojet is modeled by a linear, parameter-varying structure, and variable structure sliding mode control has been selected to control the system, as it offers excellent disturbance rejection and provides robustness against discrepancies between mathematical model and real plant as well. Both model and control system have been created in MATLAB® Simulink®, data from real measurement have been taken to evaluate control system performance. The same assessment is conducted with conventional Proportional-Integral-Derivative (PID) controllers and showed the superiority of SMC, furthermore TPR computation using turbine discharge temperature was proven. Based on the results of the simulation, a controller layout is proposed and its feasibility is investigated. The utilization of TPR results in more accurate thrust output, meanwhile it allows better insight into the thermodynamic process of the engine, hence it carries an additional diagnostic possibility.

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Closed-loop data-driven modeling and distributed control for islanded microgrids with input constraints

Zheng

Madani²,

Karimi³

2022

Control Engineering Practice

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Hybrid position–admittance realization of an adaptive output super-twisting controller for a robotic scalpel

Cited by 5 publications

References 22 publications

Radial basis function neural network based second-order sliding mode control for robotic manipulator

Radial basis function neural network based second-order sliding mode control for robotic manipulator

Sliding Mode Control for Micro Turbojet Engine Using Turbofan Power Ratio as Control Law

Closed-loop data-driven modeling and distributed control for islanded microgrids with input constraints

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