A Two-Layer Trajectory Tracking Control Scheme of Manipulator Based on ELM-SMC for Autonomous Robotic Vehicle

Wang, Xingyu; Wang, Dazhi; Du, Mingtian; Song, Kaijun; Ni, Yongliang; Liu, Yanming

doi:10.1109/tase.2023.3238349

Cited by 6 publications

(3 citation statements)

References 38 publications

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“…In this method, the weight of the sliding surface is adaptively scheduled according to the stability index [164]. Wang et al design the high-order sliding mode to effectively reduce system chattering and improve control accuracy [165]. As high-order sliding modes suffer from computation workload, the second-order sliding mode remains the mainstream to ensure the real-time performance of the algorithm.…”

Section: B Feedback Control Algorithms Without Predictionmentioning

confidence: 99%

A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles

Liu,

Hua,

Deng

et al. 2023

IEEE Internet Things J.

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Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger comfort, transportation efficiency, and energy saving. This survey attempts to provide a comprehensive and thorough overview of the current state of vehicle control technology, focusing on the evolution from vehicle state estimation and trajectory tracking control in AVs at the microscopic level to collaborative control in CAVs at the macroscopic level. First, this review starts with vehicle key state estimation, specifically vehicle sideslip angle, which is the most pivotal state for vehicle trajectory control, to discuss representative approaches. Then, we present symbolic vehicle trajectory tracking control approaches for AVs. On top of that, we further review the collaborative control frameworks for CAVs and corresponding applications. Finally, this survey concludes with a discussion of future research directions and the challenges. This survey aims to provide a contextualized and indepth look at the state of the art in vehicle control for AVs and CAVs, identifying critical areas of focus and pointing out the potential areas for further exploration.

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Section: B Feedback Control Algorithms Without Predictionmentioning

confidence: 99%

A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles

Liu,

Hua,

Deng

et al. 2023

IEEE Internet Things J.

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show abstract

“…In addition to automatic movement, the robotic manipulator drive system must also be automated for autonomous driving of robotic vehicles. In order to more correctly describe the joint space movement of the manipulator system under multitask coupling and external interference, the work [26] offered an adaptive trajectory tracking control of the manipulator based on sliding mode control.…”

Section: Introductionmentioning

confidence: 99%

A Generalized Supertwisting Algorithm Based on Terminal Sliding Manifold Control of Perturbed Unicycle Mobile Robots

Boubaker,

Labbadi,

Alsubaei

2024

IEEE Access

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This paper addresses the topic of stabilizing a class of nonholonomic systems in chained form impacted by matched uncertainties and time-varying perturbations. To design efficient stabilizing control law, the whole problem is divided into two sub-problems. The first sub-problem considers a system with perturbation stabilized using a fixed-time controller. The second sub-problem consists of the design of a controller for a second system operating under perturbations and uncertainties. To control this second system, firstly a terminal sliding mode manifold is proposed to achieve a fixed-time stability. As opposed to the traditional supertwisting algorithm (STA), the present work proposes a generalized STA (GSTA). The proposed method's most striking feature is the substitution of a fractional power term for the standard STA's discontinuous term, which can significantly boost the former's performance. It is demonstrated that the GSTA will reduce to the traditional STA if the fractional power in the nonsmooth term equals −1/2. The ability of the sliding variables to finite-time converge to an arbitrary tiny region in the vicinity of the origin by adjusting the gains and the fractional power will be thoroughly proven under the GSTA by utilizing strict Lyapunov analysis. The effectiveness of the proposed control method is shown through extensive simulations.INDEX TERMS Perturbed unicycle mobile robots, Nonholonomic systems, Fixed-time/finite stabilization, Lyapunov methods, high order sliding mode, Perturbations.

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“…Therefore, higher-order is the most common type for vehicle controllers that use SMC theory, as in [21], [26], [32]. Other recent SMC strategies include fractional-order [27], [33], [34] and the use of machine learning combined with SMC [25], [35]- [37]. Whereas MPC can accommodate vehicle nonlinearities and multiple hard and soft constraints, its main disadvantage is the high computational cost, which can be unsuitable for real-time applications [38].…”

Section: Introductionmentioning

confidence: 99%

Coupled Lateral and Longitudinal Controller for Over-Actuated Vehicle in Evasive Maneuvering With Sliding Mode Control Strategy

et al. 2023

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A Two-Layer Trajectory Tracking Control Scheme of Manipulator Based on ELM-SMC for Autonomous Robotic Vehicle

Cited by 6 publications

References 38 publications

A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles

A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles

A Generalized Supertwisting Algorithm Based on Terminal Sliding Manifold Control of Perturbed Unicycle Mobile Robots

Coupled Lateral and Longitudinal Controller for Over-Actuated Vehicle in Evasive Maneuvering With Sliding Mode Control Strategy

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