Fuzzy Sliding Mode Controller for Dynamic Nonlinear Systems

Kumawat, Gaurav; Vajpai, Jayashri

doi:10.1007/978-3-319-52503-7_18

Intelligent Human Computer Interaction

2017

DOI: 10.1007/978-3-319-52503-7_18

|View full text |Cite

Fuzzy Sliding Mode Controller for Dynamic Nonlinear Systems

Gaurav Kumawat

Jayashri Vajpai

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2023

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A Survey of Intelligent Driving Vehicle Trajectory Tracking Based on Vehicle Dynamics

Zha¹,

Deng²,

Qiu³

et al. 2023

SAE Int. J. Veh. Dyn., Stab., and NVH

View full text Add to dashboard Cite

<div>Trajectory tracking control, as one of the core technologies of intelligent driving vehicles, determines the driving performance and safety of intelligent driving vehicles and has received extensive attention and research. In recent years, most of the research results of trajectory tracking control are only applicable to conventional working conditions; however, the actual operating conditions of intelligent driving vehicles are complex and variable, so the research of trajectory tracking control algorithm should be extended to the high-speed low-adhesion coefficient, large curvature, variable curvature, and other compound limit working conditions. This requires more consideration of the vehicle dynamics in the controller design. In this article, a comprehensive review of trajectory tracking control under extreme operating conditions is conducted from three levels: vehicle dynamics model, vehicle speed tracking (longitudinal motion control), and path tracking (transverse motion control), and the existing research results are analyzed and summarized to obtain the research trends and pain points and difficulties in each field. On this basis, the future outlook of trajectory tracking control is proposed, which is expected to provide some help and inspiration to the research workers in this field.</div>

show abstract

A Survey of Intelligent Driving Vehicle Trajectory Tracking Based on Vehicle Dynamics

Zha¹,

Deng²,

Qiu³

et al. 2023

SAE Int. J. Veh. Dyn., Stab., and NVH

View full text Add to dashboard Cite

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.

Fuzzy Sliding Mode Controller for Dynamic Nonlinear Systems

Cited by 1 publication

References 5 publications

A Survey of Intelligent Driving Vehicle Trajectory Tracking Based on Vehicle Dynamics

A Survey of Intelligent Driving Vehicle Trajectory Tracking Based on Vehicle Dynamics

Contact Info

Product

Resources

About