Robust Control for a Two DOF Robot Manipulator

Massaoudi, Fatma; Elleuch, Dorsaf; Damak, Tarak

doi:10.1155/2019/3919864

Cited by 8 publications

(8 citation statements)

References 13 publications

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“…𝜏𝜏 = 𝑀𝑀(𝜃𝜃)�𝜃𝜃 ̈𝑖𝑖 − λ𝑒𝑒� + 𝐶𝐶�𝜃𝜃, 𝜃𝜃 �𝜃𝜃 ̇+ 𝑔𝑔(𝜃𝜃) − 𝑀𝑀(𝜃𝜃)𝐾𝐾. 𝑉𝑉(𝑆𝑆) (26) where: 𝑉𝑉(𝑆𝑆) = [𝑉𝑉 1 (𝑆𝑆 1 ) 𝑉𝑉 2 (𝑆𝑆 2 )] 𝑇𝑇 . We consider in the simulation three forms of the function 𝑉𝑉 𝑖𝑖 (𝑆𝑆 𝑖𝑖 ): 𝑠𝑠𝑖𝑖𝑔𝑔𝑠𝑠(𝑆𝑆 𝑖𝑖 ), 𝑠𝑠𝑑𝑑𝑑𝑑(𝑆𝑆 𝑖𝑖 /𝜑𝜑 𝑖𝑖 ) and 𝑑𝑑𝑑𝑑𝑠𝑠ℎ(𝑆𝑆 𝑖𝑖 /𝛼𝛼 𝑖𝑖 ).…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…To eliminate or reduce this chattering phenomenon, there is a solution in the literature that consists in smoothing the 𝑠𝑠𝑖𝑖𝑔𝑔𝑠𝑠(𝑆𝑆) function near the 0 point, replacing it with a continuous function that has a similar appearance, such as the saturation function and the hyperbolic tangent function used in [24]. The general form of the saturation function 𝑠𝑠𝑑𝑑𝑑𝑑(𝑆𝑆 𝑖𝑖 /𝜑𝜑 𝑖𝑖 ) [25,26] and the hyperbolic tangent function 𝑑𝑑𝑑𝑑𝑠𝑠ℎ(𝑆𝑆 𝑖𝑖 /𝛼𝛼 𝑖𝑖 ) [27] is given by:…”

Section: Chattering Phenomenonmentioning

confidence: 99%

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Optimization of the Performances of a Two-Joint Robotic Arm using Sliding Mode Control

Bendimrad

AMRANI

2022

Int. J. Automot. Mech. Eng.

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In this paper, we worked on the control of the angular position of a two-joint robotic arm by the sliding mode technique, after having establishing the dynamic equations of the system by the Lagrange method, with the purpose of improving the performances of the system by acting on certain parameters related to the sliding mode technique. The simulation results show an optimization of the sliding mode controller parameters, generally, in the response of the controlled system, which consists on minimizing error and settling time, and eliminating the unwanted phenomenon of chattering, after finding the optimal values of these parameters. Verification by simulation of the robustness of the optimized robotic arm shows that its response is independent of the dimensions and masses of the bodies of this robotic arm, as well as of the applied load. this answer always corresponds to the best performances of speed, settling time and margin of error. the only quantity that varies according to the parameters of the robotic arm and the applied load is the torque required. This couple has a compensating effect to the change of these internal parameters and of this applied load, to keep the same optimal response on the condition of communicating these changes with the controller.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Chattering Phenomenonmentioning

confidence: 99%

Optimization of the Performances of a Two-Joint Robotic Arm using Sliding Mode Control

Bendimrad

AMRANI

2022

Int. J. Automot. Mech. Eng.

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“…The frame assignments for the 3-DOF articulated robotic arm showing the various joints and their links are shown in Figure 1 (Massaoudi et al, 2019). The DH parameters for the 3-DOF robotic manipulator are presented in Table 1.…”

Section: Kinematic Modeling Of Robot Manipulatormentioning

confidence: 99%

Modeling and control of a 3-DOF articulated robotic manipulator using self-tuning fuzzy sliding mode controller

2021

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Robotic manipulators are highly coupled multi-input multi-output (MIMO) nonlinear systems with uncertainties and highly time-varying dynamic capabilities. These characteristics make the trajectory control of a robotic manipulator very challenging. This paper presents the modeling and trajectory tracking control of a 3-DOF robotic manipulator using self-tuning fuzzy sliding mode controller (ST-FSMC). The stability of the system was investigated using the Lyapunov direct method. The controller was implemented using MATLAB/Simulink and its performance was evaluated. The simulation results show that the proposed controller removed chattering phenomena from the control effort and reduced the tracking error (average steady-state error) to 0.0036 rad. However, in the case of the conventional controllers, the average steady-state error increased to 0.0413 rad, 0.0044 rad, and 0.0053 rad for the Proportional-integral-derivative (PID) controller, Sliding mode controller (SMC), and Fuzzy sliding mode controller (FSMC), respectively. The conventional controllers (PID, SMC, and FSMC) were designed for the Aderajew Ashagrie

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“…The basic idea of the backstepping method is to analyze the system and to design the controller which makes the error dynamics stable. Specially, it is applied to the globally stable and asymptotically adaptive tracking control of a strict feedback nonlinear system [29]. In [29], a backstepping controller is adopted to control a manipulator robot.…”

Section: Introductionmentioning

confidence: 99%

Backstepping Controller for Mobile Robot in Presence of Disturbances and Uncertainties

Hassani,

Rekik

2023

IJRCS

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The objective of this work is to devise an effective control system for addressing the trajectory tracking challenge in nonholonomic mobile robots. Two primary control approaches, namely kinematic and dynamic strategies, are explored to achieve this goal. In the kinematic control domain, a backstepping controller (BSC) is introduced as the core element of the control system. The BSC is utilized to guide the mobile robot along the desired trajectory, leveraging the robot’s kinematic model. To address the limitations of the kinematic control approach, a dynamic control strategy is proposed, incorporating the dynamic parameters of the robot. This dynamic control ensures real-time control of the mobile robot. To ensure the stability of the control system, the Lyapunov stability theory is employed, providing a rigorous framework for analyzing and proving stability. Additionally, to optimize the performance of the control system, a genetic algorithm is employed to design an optimal control law. The effectiveness of the developed control approach is demonstrated through simulation results. These results showcase the enhanced performance and efficiency achieved by the proposed control strategies. Overall, this study presents a comprehensive and robust approach for trajectory tracking in nonholonomic mobile robots, combining kinematic and dynamic control strategies while ensuring stability and performance optimization.

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Robust Control for a Two DOF Robot Manipulator

Cited by 8 publications

References 13 publications

Optimization of the Performances of a Two-Joint Robotic Arm using Sliding Mode Control

Optimization of the Performances of a Two-Joint Robotic Arm using Sliding Mode Control

Modeling and control of a 3-DOF articulated robotic manipulator using self-tuning fuzzy sliding mode controller

Backstepping Controller for Mobile Robot in Presence of Disturbances and Uncertainties

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