CASIA OpenIR
A Novel Neural-Network-Based Adaptive Control Scheme for Output-Constrained Stochastic Switched Nonlinear Systems
Niu, Ben1; Wang, Ding2; Li, Huan1; Xie, Xuejun3; Alotaibi, Naif D.4; Alsaadi, Fuad E.4
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
ISSN2168-2216
2019-02-01
Volume49Issue:2Pages:418-432
Corresponding AuthorNiu, Ben(niubenbhu@gmail.com)
AbstractIn this paper, a novel neural-network (NN)-based adaptive tracking controller design method is presented for the single-input/single-output nonlinear stochastic switched systems in lower triangular structures with an output constraint. First, a well-designed nonlinear mapping is introduced to transform the switched stochastic system to a new system without constraints, which implies the controller design of the transformed system is equivalent to that of the stochastic switched system. Then radial basis function NNs are applied to model the unknown nonlinearities and the adaptive backstepping technique is employed to construct two classes of adaptive neural controllers under different adaptive laws. It is proved that both controllers can assure all the signals in the closed-loop remain bounded in probability, and the tracking error finally converges to a neighborhood of the origin without violating the constraint. Furthermore, the use of the nonlinear mapping to deal with the asymmetric output constraint is also studied as a generalization result. Two illustrative examples with numerical data and simulation results are given to show the validity and performance of the proposed control schemes.
KeywordAdaptive control neural network (NN) nonlinear mapping output constraints stochastic switched systems
DOI10.1109/TSMC.2017.2777472
WOS KeywordTRACKING CONTROL ; HOMOGENEOUS DOMINATION ; STABILITY ANALYSIS ; FEEDBACK CONTROL ; STATE-FEEDBACK ; ROBUST-CONTROL ; FUZZY ; STABILIZATION ; OBSERVER ; DESIGN
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61673073] ; National Natural Science Foundation of China[61673242] ; Liaoning Provincial Natural Science Foundation, China[201602009]
Funding OrganizationNational Natural Science Foundation of China ; Liaoning Provincial Natural Science Foundation, China
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000457670800013
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:14[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/25288
Collection中国科学院自动化研究所
Corresponding AuthorNiu, Ben
Affiliation1.Bohai Univ, Coll Math & Phys, Jinzhou 121013, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Qufu Normal Univ, Inst Automat, Qufu 273165, Peoples R China
4.King Abdulaziz Univ, Fac Engn, Dept Elect & Comp Engn, Jeddah 21589, Saudi Arabia
Recommended Citation
GB/T 7714
Niu, Ben,Wang, Ding,Li, Huan,et al. A Novel Neural-Network-Based Adaptive Control Scheme for Output-Constrained Stochastic Switched Nonlinear Systems[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2019,49(2):418-432.
APA Niu, Ben,Wang, Ding,Li, Huan,Xie, Xuejun,Alotaibi, Naif D.,&Alsaadi, Fuad E..(2019).A Novel Neural-Network-Based Adaptive Control Scheme for Output-Constrained Stochastic Switched Nonlinear Systems.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,49(2),418-432.
MLA Niu, Ben,et al."A Novel Neural-Network-Based Adaptive Control Scheme for Output-Constrained Stochastic Switched Nonlinear Systems".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 49.2(2019):418-432.
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