Construction and management of smart campus: Anti-disturbance control of flexible manipulator based on PDE modeling

Wei, Yuanyuan; Zhang, Yuanfei; Hang, Bin

doi:10.3934/mbe.2023641

MBE

2023

DOI: 10.3934/mbe.2023641

|View full text |Cite

Construction and management of smart campus: Anti-disturbance control of flexible manipulator based on PDE modeling

Yuanyuan Wei

Yuanfei Zhang²,

Bin Hang

Abstract: <abstract><p>With the rapid development of smart campus, this paper studies the attitude tracking control of flexible manipulator (FM) in colleges and universities under elastic vibration and external disturbances. First, different from the traditional modeling based on ordinary differential equations (ODEs), the partial differential equations (PDEs) dynamic model of a manipulator system is established based on the Hamilton principle (HP). Second, the boundary control condition of the end system of… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Dual-loop control and state prediction analysis of QUAV trajectory tracking based on biological swarm intelligent optimization algorithm

Zou,

Yang,

Zhao

2024

Sci Rep

View full text Add to dashboard Cite

Quadrotor unmanned aerial vehicles (QUAVs) have attracted significant research focus due to their outstanding Vertical Take-Off and Landing (VTOL) capabilities. This research addresses the challenge of maintaining precise trajectory tracking in QUAV systems when faced with external disturbances by introducing a robust, two-tier control system based on sliding mode technology. For position control, this approach utilizes a virtual sliding mode control signal to enhance tracking precision and includes adaptive mechanisms to adjust for changes in mass and external disruptions. In controlling the attitude subsystem, the method employs a sliding mode control framework that secures system stability and compliance with intermediate commands, eliminating the reliance on precise models of the inertia matrix. Furthermore, this study incorporates a deep learning approach that combines Particle Swarm Optimization (PSO) with the Long Short-Term Memory (LSTM) network to foresee and mitigate trajectory tracking errors, thereby significantly enhancing the reliability and safety of mission operations. The robustness and effectiveness of this innovative control strategy are validated through comprehensive numerical simulations.

show abstract

Dual-loop control and state prediction analysis of QUAV trajectory tracking based on biological swarm intelligent optimization algorithm

Zou,

Yang,

Zhao

2024

Sci Rep

View full text Add to dashboard Cite

show abstract

Robust tracking control of a flexible manipulator with limited control input based on backstepping and the Nussbaum function

Tan,

Chen,

2023

MBE

View full text Add to dashboard Cite

<abstract><p>A flexible manipulator is a versatile automated device with a wide range of applications, capable of performing various tasks. However, these manipulators are often vulnerable to external disturbances and face limitations in their ability to control actuators. These factors significantly impact the precision of tracking control in such systems. This study delves into the problem of attitude tracking control for a flexible manipulator under the constraints of control input limitations and the influence of external disturbances. To address these challenges effectively, we first introduce the backstepping method, aiming to achieve precise state tracking and tackle the issue of external disturbances. Additionally, recognizing the constraints posed by control input limitations in the flexible manipulator's actuator control system, we employ a design approach based on the Nussbaum function. This method is designed to overcome these limitations, allowing for more robust control. To validate the effectiveness and disturbance rejection capabilities of the proposed control strategy, we conduct comparative numerical simulations using MATLAB/Simulink. These simulations provide further evidence of the robustness and reliability of the control strategy, even in the presence of external disturbances and control input limitations.</p></abstract>

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Construction and management of smart campus: Anti-disturbance control of flexible manipulator based on PDE modeling

Cited by 2 publications

References 46 publications

Dual-loop control and state prediction analysis of QUAV trajectory tracking based on biological swarm intelligent optimization algorithm

Dual-loop control and state prediction analysis of QUAV trajectory tracking based on biological swarm intelligent optimization algorithm

Robust tracking control of a flexible manipulator with limited control input based on backstepping and the Nussbaum function

Contact Info

Product

Resources

About