A direct robust nonsingular terminal sliding mode controller based on an adaptive time-delay estimator for servomotor rigid robots

Ba, Dang Xuan; Yeom, Hoyeon; Bae, Joonbum

doi:10.1016/j.mechatronics.2019.03.007

Cited by 23 publications

(31 citation statements)

References 29 publications

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“…As noted in [35], the transient control quality of the sliding phase is improved by employing the nonlinear sliding manifold (4). However, this effect is diminished when the control errors approach to the origin.…”

Section: Remarkmentioning

confidence: 99%

“…The bound (18) and the learn rule (16) reveal that the high-level variation gains 1 2 ( , ) k k ⌣ ⌣ work as activedisturbance-compensation terms in the reaching phase, while the sliding-gain variation 0 ( ) k ⌣ would strongly activate in the sliding phase or as the sliding manifold is inside a certain range. Different from previous works [35], [39], the learning law (14) is designed such that the variation gains 1 2 ( , ) k k ⌣ ⌣ are respectively strongly activated in two specific ranges of the sliding manifold.…”

Section: Remarkmentioning

confidence: 99%

“…A conventional TDE is employed to eliminate influence of the system dynamics on the control performance. By extending results of the previous work [35], a new sliding mode manifold is designed by synthesizing various information of the control error as an indirect control objective in a low-level control layer. A basic sliding-mode control rule is adopted as a high-level control layer to stabilize the manifold around the origin using driving and robust control signals.…”

Section: Introductionmentioning

confidence: 96%

“…Flexibility of the controller operation has been improved but the terminal or supertwisting SMC schemes provided excellent control performances only in mall-attraction regions around the origin. Their transient-convergence rates of reaching and sliding phases were also slower than those of the linear SMC [34][35]. Furthermore, ones still need to tune the sliding gains for different working conditions.…”

Section: Introductionmentioning

confidence: 99%

“…The learning law of the sliding gain is proposed in the low-level control layer for improving the state-state control accuracy. 2) Inspired from previous works [35], [39], learning laws of the high-level control layer are modified for improving the reaching control performance. An adaptation mechanism of the driving and robust gains is designed to separately excite for large and small ranges of the sliding surfaces, respectively.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Nonlinear Sliding Mode Controller of Serial Robot Manipulators With Two-Level Gain-Learning Ability

Bae

2020

IEEE Access

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This paper presents a learning robust controller for high-quality position tracking control of robot manipulators. A basic time-delay estimator is adopted to effectively approximate the system dynamics. A low-level control layer is structured from the control error as an indirect control objective using new nonlinear sliding-mode synthetization. To realize the control objective with desired transient time, a robust sliding mode control signal is then designed based on the obtained estimation results in a high-level control layer. To promptly suppress unpredictable disturbances, adaptation ability is integrated to the controller using two-level gain-learning laws. Reaching gains and sliding gain are automatically tuned for asymptotic control performance. Effectiveness of the designed controller is concretely confirmed by the Lyapunov-based stability criterion, comparative simulations, and real-time experiments. INDEX TERMS manipulators, gain adaptive control, nonlinear sliding mode, position control, robust adaptive control, time-delay estimation.

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Section: Remarkmentioning

confidence: 99%

Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Nonlinear Sliding Mode Controller of Serial Robot Manipulators With Two-Level Gain-Learning Ability

Bae

2020

IEEE Access

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An intelligent sliding mode controller of robotic manipulators with output constraints and high‐level adaptation

2022

Intl J Robust & Nonlinear

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Fast transient responses and excellent steady-state control performances with flexibility in control operation are core motivations to promote a vast of research in the robotic control sector nowadays. As a sequence, in this paper, we present a learning nonlinear controller for motion control of robotic manipulators with output constraints. The constrained control objectives are first transformed to new free variables using nonlinear synthetization profiles. Boundedness of the main control objectives within feasible ranges of the physical outputs is next strictly guaranteed under a simple sliding-mode control policy. To improve the control performance, dominant terms of the system dynamics are learnt by a neural network with a nonlinear adaptation law. The systematic deviation remaining is then estimated by an adaptive disturbance observer. A novel high-level adaptation rule is designed to maximize the learning ability and the control quality. Both an asymptotic control performance and estimation effectiveness are theoretically thoroughly proven by Lyapunov-based analyses. Feasibility of the overall system is carefully investigated by intensive comparative simulations.

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A model free adaptive‐robust design for control of robot manipulators: Time delay estimation approach

Taefi,

Khosravi

2024

Intl J Robust & Nonlinear

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SummaryThis paper addresses a new robust control scheme for tracking control of the robot manipulators. This algorithm employs time delay estimation (TDE) technique in combination with backstepping control strategy. The suggested control scheme has no dependency on the robot dynamic model and knowing the bound of the inertia matrix is enough to develop this controller. To develop the idea, at first the boundedness of the TDE errors is analyzed by Lyapunov‐Krasovskii approach. Next, the proposed TDE based adaptive backstepping nonsingular terminal sliding mode control (ABNTSMC) algorithm is developed. In this way, a novel adaptive‐robust term is employed to defeat the chattering phenomenon. Moreover, the closed‐loop stability of the system is proven through Lyapunov second approach. Fast transient response, supreme robustness, and chattering‐free as the premier specifications are gained employing the proposed control algorithm. The efficiency of the suggested control scheme is illustrated through some simulations on an industrial robot and the results are compared with some other control algorithms. Finally, the practical effectiveness of the proposed TDE based control algorithm is verified through some experiments on a parallelogram robot manipulator.

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A direct robust nonsingular terminal sliding mode controller based on an adaptive time-delay estimator for servomotor rigid robots

Cited by 23 publications

References 29 publications

A Nonlinear Sliding Mode Controller of Serial Robot Manipulators With Two-Level Gain-Learning Ability

A Nonlinear Sliding Mode Controller of Serial Robot Manipulators With Two-Level Gain-Learning Ability

An intelligent sliding mode controller of robotic manipulators with output constraints and high‐level adaptation

A model free adaptive‐robust design for control of robot manipulators: Time delay estimation approach

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