Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems

Qiao Lin; Qinglai Wei; Derong Liu

doi:10.1109/CCDC.2016.7531890

Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems

Qiao Lin, Qinglai Wei, Derong Liu

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

This paper deals with optimal tracking control problems for a class of discrete-time nonlinear systems using a generalized policy iteration adaptive dynamic programming (ADP) algorithm. First, by system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. Then the generalized policy iteration ADP algorithm is employed to obtain the optimal tracking controller with convergence and optimality analysis. The developed algorithm uses the idea of two iteration procedures to obtain the iterative tracking control laws and the iterative value functions. Three neural networks, including model network, critic network and action network, are used to implement the developed algorithm. At last, an simulation example is given to demonstrate the effectiveness of the developed method.

Original language	English
Title of host publication	Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	5009-5014
Number of pages	6
ISBN (Electronic)	9781467397148
DOIs	https://doi.org/10.1109/CCDC.2016.7531890
Publication status	Published - 3 Aug 2016
Externally published	Yes
Event	28th Chinese Control and Decision Conference, CCDC 2016 - Yinchuan, China Duration: 28 May 2016 → 30 May 2016

Publication series

Name	Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016

Conference

Conference	28th Chinese Control and Decision Conference, CCDC 2016
Country/Territory	China
City	Yinchuan
Period	28/05/16 → 30/05/16

Keywords

adaptive dynamic programming
affine nonlinear systems
discrete-time
generalized policy iteration
neural network
tracking control

ASJC Scopus subject areas

Control and Systems Engineering
Control and Optimization
Statistics, Probability and Uncertainty
Artificial Intelligence
Decision Sciences (miscellaneous)

Access to Document

10.1109/CCDC.2016.7531890

Cite this

Lin, Q., Wei, Q., & Liu, D. (2016). Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems. In Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016 (pp. 5009-5014). Article 7531890 (Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC.2016.7531890

Lin, Qiao ; Wei, Qinglai ; Liu, Derong. / Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems. Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 5009-5014 (Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016).

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title = "Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems",

abstract = "This paper deals with optimal tracking control problems for a class of discrete-time nonlinear systems using a generalized policy iteration adaptive dynamic programming (ADP) algorithm. First, by system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. Then the generalized policy iteration ADP algorithm is employed to obtain the optimal tracking controller with convergence and optimality analysis. The developed algorithm uses the idea of two iteration procedures to obtain the iterative tracking control laws and the iterative value functions. Three neural networks, including model network, critic network and action network, are used to implement the developed algorithm. At last, an simulation example is given to demonstrate the effectiveness of the developed method.",

keywords = "adaptive dynamic programming, affine nonlinear systems, discrete-time, generalized policy iteration, neural network, tracking control",

author = "Qiao Lin and Qinglai Wei and Derong Liu",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 28th Chinese Control and Decision Conference, CCDC 2016 ; Conference date: 28-05-2016 Through 30-05-2016",

year = "2016",

month = aug,

day = "3",

doi = "10.1109/CCDC.2016.7531890",

language = "English",

series = "Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "5009--5014",

booktitle = "Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016",

address = "United States",

}

Lin, Q, Wei, Q & Liu, D 2016, Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems. in Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016., 7531890, Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016, Institute of Electrical and Electronics Engineers Inc., pp. 5009-5014, 28th Chinese Control and Decision Conference, CCDC 2016, Yinchuan, China, 28/05/16. https://doi.org/10.1109/CCDC.2016.7531890

Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems. / Lin, Qiao; Wei, Qinglai; Liu, Derong.
Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 5009-5014 7531890 (Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems

AU - Lin, Qiao

AU - Wei, Qinglai

AU - Liu, Derong

PY - 2016/8/3

Y1 - 2016/8/3

N2 - This paper deals with optimal tracking control problems for a class of discrete-time nonlinear systems using a generalized policy iteration adaptive dynamic programming (ADP) algorithm. First, by system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. Then the generalized policy iteration ADP algorithm is employed to obtain the optimal tracking controller with convergence and optimality analysis. The developed algorithm uses the idea of two iteration procedures to obtain the iterative tracking control laws and the iterative value functions. Three neural networks, including model network, critic network and action network, are used to implement the developed algorithm. At last, an simulation example is given to demonstrate the effectiveness of the developed method.

AB - This paper deals with optimal tracking control problems for a class of discrete-time nonlinear systems using a generalized policy iteration adaptive dynamic programming (ADP) algorithm. First, by system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. Then the generalized policy iteration ADP algorithm is employed to obtain the optimal tracking controller with convergence and optimality analysis. The developed algorithm uses the idea of two iteration procedures to obtain the iterative tracking control laws and the iterative value functions. Three neural networks, including model network, critic network and action network, are used to implement the developed algorithm. At last, an simulation example is given to demonstrate the effectiveness of the developed method.

KW - adaptive dynamic programming

KW - affine nonlinear systems

KW - discrete-time

KW - generalized policy iteration

KW - neural network

KW - tracking control

UR - http://www.scopus.com/inward/record.url?scp=84983757012&partnerID=8YFLogxK

U2 - 10.1109/CCDC.2016.7531890

DO - 10.1109/CCDC.2016.7531890

M3 - Conference contribution

T3 - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016

SP - 5009

EP - 5014

BT - Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 28th Chinese Control and Decision Conference, CCDC 2016

Y2 - 28 May 2016 through 30 May 2016

ER -

Lin Q, Wei Q, Liu D. Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems. In Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 5009-5014. 7531890. (Proceedings of the 28th Chinese Control and Decision Conference, CCDC 2016). doi: 10.1109/CCDC.2016.7531890

Generalized policy iteration adaptive dynamic programming algorithm for optimal tracking control of a class of nonlinear systems

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Keywords

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