2020
DOI: 10.1177/1729881420981524
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Optimal super-twisting sliding mode control design of robot manipulator: Design and comparison study

Abstract: This article presents a tracking control design for two-link robot manipulators. To achieve robust tracking control performance, a super-twisting sliding mode control (STSMC) is derived. The stability of the system based on the proposed approach is proved based on the Lyapunov theorem. However, one problem with the designed STSMC is to properly set its parameters during the design. Therefore, it is proposed a social spider optimization (SSO) to tune these design parameters to improve the dynamic performance of… Show more

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Cited by 36 publications
(17 citation statements)
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References 55 publications
(62 reference statements)
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“…It reduces chattering and improving the control system's robustness and accuracy while maintaining nominal control efficiency. The sliding manifold š‘  = [š‘  1 š‘  2 ] š‘‡ selected for the system is [20], [21]:…”
Section: Modelling For Two Rigid Link-flexible Joint Manipulatormentioning
confidence: 99%
“…It reduces chattering and improving the control system's robustness and accuracy while maintaining nominal control efficiency. The sliding manifold š‘  = [š‘  1 š‘  2 ] š‘‡ selected for the system is [20], [21]:…”
Section: Modelling For Two Rigid Link-flexible Joint Manipulatormentioning
confidence: 99%
“…If the variable x 2 is assigned as virtual control x 2v , as defined by equation (24), then equation (26) becomes…”
Section: Backstepping Sliding Mode Controlmentioning
confidence: 99%
“…The switching part of control signal is responsible for driving states trajectory to equilibrium point by maintaining the dynamics of the system onto the sliding surface. 26,27 In the control action of the SMC, there is undesired phenomena known as chattering, which is caused by the high frequency oscillation of the sliding variable around the sliding surface, and it is one problem in using sliding mode technique. 27 The backstepping control procedure depends on the concept of simplifying the complex nonlinear system by decomposing it into lower orders subsystems.…”
Section: Introductionmentioning
confidence: 99%
“…Plenty of FB control methods have been proposed: partial feedback linearization method [13,14], adaptive control [15][16][17][18][19], model predictive control [20,21], sliding 2 ORSINI mode control [22,23], disturbance-observer-based control [24], and modal approach based on distributed mass model [25]. These techniques have been also successfully applied to mechanical systems with a similar dynamics [26,27]. Recent FB control techniques [28][29][30] have been proposed to also handle actuator deadzones/constraints and constraints on all state variables.…”
Section: Introductionmentioning
confidence: 99%