NDLI: Using Least-Square Policy Iteration to Online Optimize the Parameters of ALV's Speed Controller

Content Provider	IEEE Xplore Digital Library
Author	Qi Zhu Jian Wang Bin Dai Xin Xu
Copyright Year	2013
Description	Author affiliation: Inst. of Unmanned Syst., Nat. Univ. of Defense Tech, Changsha, China (Qi Zhu; Jian Wang; Bin Dai; Xin Xu)
Abstract	Due to the highly non-linear properties of the longitudinal dynamics of autonomous land vehicles (ALVs), it is difficult to tune the parameters of a speed controller for the autonomous driving of ALVs. Aiming at this problem, in this paper, a novel learning-Based speed controller is proposed, which is composed of a time-varying proportional-integral (PI) control structure and a learning-Based learning module. A near-optimal policy is obtained by least-square policy iteration (LSPI), which is an approximate policy iteration method. The learning-Based module uses the near-optimal policy to realize online tuning of the PI coefficients. The simulation results show that the proposed controller can optimize the control performance by combining different non-optimal coefficients of the PI structure.
Sponsorship	IEEE Nanjing Sect. CIS Chapt.
Starting Page	239
Ending Page	244
File Size	318229
Page Count	6
File Format	PDF
ISBN	9780769550114
e-ISBN	9780769550114
DOI	10.1109/IHMSC.2013.205
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-08-26
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Approximate policy iteration LSPI Velocity control Autonomous land vehicle Pi control Reinforcement learning Vectors Speed control Acceleration Mathematical model Optimization Vehicles
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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