Frictional forces and torques compensation based cascaded sliding-mode tracking control for an uncertain omnidirectional mobile robot

Wu, Hsiu-Ming; Karkoub, Mansour

doi:10.1177/00202940221092033

Cited by 7 publications

(2 citation statements)

References 20 publications

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“…[16], [17], [18]) and sliding-mode control techniques (Refs. [19], [20], [21]). However, these approaches required numerous sensors including velocity, acceleration, torque, or current sensors to be installed in the robot for successful implementation.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, dissimilar to Refs. [8], [9], [10], [11], [12], [15], [16], [17], [18], [19], [20], and [21], the trajectory tracking is achieved by using a feedback from the position of the package and the control inputs are actuated on each conveyor module independently via actuator voltages. 3) A mission for collision avoidance between packages is successfully achieved.…”

Section: Introductionmentioning

confidence: 99%

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Intelligent Motion Control Design for an Omnidirectional Conveyor System

Zaman

2023

IEEE Access

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Nowadays, an omnidirectional conveyor system has been introduced as a new means of package transportation. The aim of this study is to achieve trajectory-tracking and collision avoidance of multiple packages which has not been done before on an omnidirectional conveyor platform. Despite the kinematic similarity to omnidirectional mobile robots which have built-in sensors to measure velocities and accelerations, this system only measures the position of the transported package via external sensors which makes it a unique and intriguing area of research. To tackle this challenge, this study employs the proposed Fuzzy Sliding-mode Tracking Control (FSTC) and Fuzzy Inter-package Collision Avoidance (FICA) schemes. The FSTC has been enhanced with fuzzy sliding surfaces that take tracking errors as control inputs and linear forces as control outputs. Furthermore, using a fuzzified package distance and collision angle as inputs, the inference engine of FICA is designed to generate the deflection angle and force gain as outputs. Additionally, the conveyor platform is modeled and built by a multiple modular omnidirectional wheel system including the conveyor and actuator dynamics. To determine its desired motion trajectory, a planned 4th-order Bèzier curve is utilized. Then, to assess the effectiveness and robustness of the proposed methods, simulations are conducted under diverse conditions. The results indicate that the package position converges within a finite time frame, highlighting the superior trajectory-tracking capabilities of FSTC in spite of any disturbances injected into position feedback signals. Meanwhile, the proposed FICA has demonstrated its effectiveness by enabling the package to navigate through the omnidirectional conveyor platform while avoiding both stationary and moving obstacles.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Intelligent Motion Control Design for an Omnidirectional Conveyor System

Zaman

2023

IEEE Access

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Design of position controller for dicing saw chuck table based on improved LADRC technology

Liang,

Xie,

Lan

et al. 2024

Microsyst Technol

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Accurate trajectory tracking control with adaptive neural networks for omnidirectional mobile robots subject to unmodeled dynamics

Lima

Moreira

Bessa

2022

J Braz. Soc. Mech. Sci. Eng.

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Omnidirectional mobile robots have gained a lot of attention in recent years due to their maneuverability capabilities. However, ensuring accurate trajectory tracking with this class of robots is still challenging control system designers. In this work, a novel intelligent controller is introduced for accurate trajectory tracking of omnidirectional robots subject to unstructured uncertainties. An adaptive neural network is adopted within a Lyapunov-based nonlinear control scheme to deal with frictional forces and other unmodeled dynamics or external disturbances that may occur. Online learning, rather than supervised offline training, is employed to allow the robot to learn on its own how to compensate for uncertainties and disturbances by interacting with the environment. The adoption of a combined error signal as the single input in the neural network significantly reduces the computational complexity of the disturbance compensation scheme and enables the resulting intelligent controller to be implemented in the embedded hardware of mobile robots. The boundedness and convergence properties of the proposed control scheme are proved by means of a Lyapunov-like stability analysis. The effectiveness of the proposed intelligent controller is numerically evaluated and experimentally validated using an omnidirectional mobile robot. The comparative analyses of the obtained results show that the adoption of an intelligent compensation scheme based on adaptive neural networks allows reductions of more than $$95\%$$ 95 % in the tracking error, thus guaranteeing an accurate tracking and confirming the great superiority of the proposed control strategy.

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Frictional forces and torques compensation based cascaded sliding-mode tracking control for an uncertain omnidirectional mobile robot

Cited by 7 publications

References 20 publications

Intelligent Motion Control Design for an Omnidirectional Conveyor System

Intelligent Motion Control Design for an Omnidirectional Conveyor System

Design of position controller for dicing saw chuck table based on improved LADRC technology

Accurate trajectory tracking control with adaptive neural networks for omnidirectional mobile robots subject to unmodeled dynamics

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