Fast terminal sliding mode tracking control of nonlinear uncertain mass–spring system with experimental verifications

Amirkhani, Saeed; Mobayen, Saleh; Iliaee, Nahal; Boubaker, Olfa; Kani, Hassan Hossein Nia

doi:10.1177/1729881419828176

Cited by 42 publications

(30 citation statements)

References 56 publications

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“…The path planning should be conducted by using the wellknown algorithms, then compare with the proposed optimal recursive algorithm in this study. Some other methodologies of the path tracking control can be studied and applied to the 3RRR robot such as a finitetime tracker for nonholonomic systems [31], fast terminal sliding mode tracking control [32], neural networks-based distributed adaptive control [33], or type-2 fuzzy-based distributed supervisory control [34].…”

Section: Future Improvementmentioning

confidence: 99%

Dynamic Filtered Path Tracking Control for a 3RRR Robot Using Optimal Recursive Path Planning and Vision-Based Pose Estimation

Huynh

Kuo

2020

IEEE Access

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This study proposes a dynamic filtered path tracking control schema for a 3RRR planar parallel robot to reduce the positioning errors caused by various sources such as backlash in the mechanical system, system nonlinearities, uncertainties, and unknown disturbances. The optimal recursive algorithm is implemented absolutely in path planning based on the optimization problem. Compared to other methods, this algorithm not only helps the robot avoid singularities but also ensures the shortest movement distance of links thanks to the optimization in path planning. The vision system using the 3D Intel RealSense camera D435i is proposed to provide the visual measurement as feedback for the pose estimation of the 3RRR planar parallel robot. The unscented Kalman filter is designed to reduce the errors of the pose estimation due to the camera's intrinsic parameters, the vibration of the mechanical system, and unknown noises. The establishment of important equations and parameters of the unscented Kalman filter is detailed in this study. The simulation, experiment, and comparison are conducted to verify the effectiveness and feasibility of the proposed approaches. INDEX TERMS 3RRR planar parallel robot, dynamic filtered path tracking control, optimal recursive path planning, vision-based pose estimation, unscented Kalman filter.

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Section: Future Improvementmentioning

confidence: 99%

Dynamic Filtered Path Tracking Control for a 3RRR Robot Using Optimal Recursive Path Planning and Vision-Based Pose Estimation

Huynh

Kuo

2020

IEEE Access

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“…The literature [29] introduced an adaptive robust finite-time control method based on a global sliding surface for the synchronization of a class of chaotic systems. The literature [30] used a fast terminal sliding mode control technique for robust tracking control of a nonlinear uncertain mass-spring system in the existence of external perturbation. In recent years, the other types of terminal sliding mode control algorithm has been proposed, including integral terminal sliding mode control method, fast sliding mode control method, nonsingular terminal sliding mode control method, exponential terminal sliding mode control method, etc.…”

Section: Introductionmentioning

confidence: 99%

Robust Continuous Sliding Mode Control for Manipulator PMSM Trajectory Tracking System Under Time-Varying Uncertain Disturbances

et al. 2020

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This paper focuses on a robust continuous sliding mode control (RCSMC) method for manipulator PMSM trajectory tracking system under time-varying uncertain disturbances. The main objective of this study is to improve the trajectory tracking dynamic response and disturbances rejection ability of the manipulator PMSM, and then the manipulator itself, by using the RCSMC method. The RCSMC method consists of two key parts: a terminal continuous sliding mode controller (TCSMC), and an extended state observer (ESO). The TCSMC has been demonstrated to have remarkable capabilities to reduce the chattering phenomenon caused by high frequency switching function in the conventional sliding mode control law, and reject the strong time-varying uncertain disturbances for PMSM velocity loops. However, the high control gain, which could lead high velocity steady state fluctuations, is needed. Therefore, an extended state observer is introduced to estimate the disturbances. The estimated disturbances are further used by the velocity loop controller as a kind of feed-forward compensation to reduce the gain of the TCSMC method. The stability of the PMSM trajectory tracking system with the RCSMC algorithm is guaranteed by the Lyapunov stability criteria. Simulations have been conducted to verify the performance of the proposed RCSMC algorithm. Finally, the proposed RCSMC algorithm is applied in a practical 6-DOF manipulator, and the experimental results exhibit the extraordinary robustness and capabilities in dynamic position tracking characteristics, velocity response and disturbances rejection. INDEX TERMS robust continuous sliding mode control, manipulator, PMSM control, trajectory tracking system,time-varying uncertain disturbances

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“…Because of the simple structure and robust behavior against parametric uncertainty and external disturbances, the sliding mode control (SMC) has become a popular method. SMC has been applied successfully to a variety of systems such as medical systems (Badfar & Ardestani, 2019;Badfar, Ardestani, & Beheshti, 2020), mechanical systems (Amirkhani, Mobayen, Iliaee, Boubaker, & Hosseinnia, 2019;Bessa, Otto, Kreuzer, & Seifried, 2019;Peza-Solis, Silva-Navarro, & Castro-Linares, 2015) and electrical converters (Asgari, 2019;Li, Liu, & Su, 2019). Recently, the terminal sliding mode control (TSMC) has been introduced to guarantee the finite-time convergence and higher precision of tracking error (Du, Chen, Wen, Yu, & Lü, 2018).…”

Section: Introductionmentioning

confidence: 99%

Design of an adaptive nonsingular terminal sliding mode using supervisory fuzzy for the output voltage control of a buck converter

Badfar¹,

Abdollahi²

2020

JART

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The buck converter is widely utilized in various applications such as solar chargers, electrical vehicles and space exploration. The use of an efficient controller in buck converters reduces the heat and losses, extends the useful life, and allows for smaller gadgets to be built. In this research, a novel technique is proposed to regulate the output voltage of the buck converter. For this purpose, the mathematical model of the converter is introduced. Next, the adaptive sliding mode is suggested to regulate the output voltage. In order to ensure the faster transient response and finite-time convergence, the terminal sliding mode control is suggested. The singularity problem is solved by using nonsingular terminal sliding mode control. The switching gain is adaptively scheduled according to the fuzzy logic system. Finally, some simulation results including the parametric uncertainties, measurement noise, and steady-state error analysis are illustrated to demonstrate the efficiency of the proposed controller.

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Fast terminal sliding mode tracking control of nonlinear uncertain mass–spring system with experimental verifications

Cited by 42 publications

References 56 publications

Dynamic Filtered Path Tracking Control for a 3RRR Robot Using Optimal Recursive Path Planning and Vision-Based Pose Estimation

Dynamic Filtered Path Tracking Control for a 3RRR Robot Using Optimal Recursive Path Planning and Vision-Based Pose Estimation

Robust Continuous Sliding Mode Control for Manipulator PMSM Trajectory Tracking System Under Time-Varying Uncertain Disturbances

Design of an adaptive nonsingular terminal sliding mode using supervisory fuzzy for the output voltage control of a buck converter

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