skip to main content
10.1145/3505688.3505701acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicraiConference Proceedingsconference-collections
research-article

Event-Triggered Intelligent Critic Design for Constrained Nonaffine Nonzero-Sum Games

Published: 09 April 2022 Publication History

Abstract

In this paper, we develop an event-triggered optimal learning algorithm based on the dual heuristic dynamic programming (DHP) framework to solve a constrained nonzero-sum game problem with discrete-time nonaffine dynamics. First, for two controllers in nonzero-sum games, we adopt different boundaries to constrain them, which ensures their independence. Then, the specific derivation process of the proposed algorithm is given by using the DHP technique. Meanwhile, an appropriate triggering condition is established to decrease the amount of computation. Finally, a simulation example is carried out to demonstrate the applicability of the constructed method. The event-based constrained control algorithm is able to substantially reduce the updating times of the control input, while still maintaining an impressive performance.

References

[1]
[1] P. J. Werbos, “Approximate dynamic programming for real-time control and neural modeling,” in Handbook of Intelligent Control: Neural, Fuzzy, and Adaptive Approaches, D. A. White and D. A. Sofge, Eds. New York: Van Nostrand Reinhold, 1992, ch. 13.
[2]
[2] D. Wang, J. Qiao, and L. Cheng, “An approximate neuro-optimal solution of discounted guaranteed cost control design,” IEEE Transactions on Cybernetics, in press, 2021.
[3]
[3] D. Liu, S. Xue, B. Zhao, B. Luo, and Q. Wei, “Adaptive dynamic programming for control: A survey and recent advances,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, vol. 51, no. 1, pp. 142–160, Jan. 2021.
[4]
[4] D. Wang, M. Ha, and J. Qiao, “Data-driven iterative adaptive critic control toward an urban wastewater treatment plant,” IEEE Transactions on Industrial Electronics, vol. 68, no. 8, pp. 7362–7369, Aug. 2021.
[5]
[5] M. Ha, D. Wang, and D. Liu, “Offline and online adaptive critic control designs with stability guarantee through value iteration,” IEEE Transactions on Cybernetics, in press, 2021.
[6]
[6] D. Liu, Q. Wei, D. Wang, X. Yang, and H. Li, “Adaptive dynamic programming with applications in optimal control,” Cham, Switzerland: Springer, 2017.
[7]
[7] A. Al-Tamimi, F. L. Lewis, and M. Abu-Khalaf, “Discrete-time nonlinear HJB solution using approximate dynamic programming: Convergence proof,” IEEE Transactions on Cybernetics, vol. 38, no. 4, pp. 943–949, Aug. 2008.
[8]
[8] H. Zhang, Y. Luo, and D. Liu, “Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints,” IEEE Transactions on Neural Networks, vol. 20, no. 9, pp. 1490–1503, Sep. 2009.
[9]
[9] D. Wang, D. Liu, Q. Wei, D. Zhao, and N. Jin, “Optimal control of unknown nonaffine nonlinear discrete-time systems based on adaptive dynamic programming,” Automatica, vol. 48, no. 8, pp. 1825–1832, 2012.
[10]
[10] D. Wang, M. Ha, and J. Qiao, “Self-learning optimal regulation for discrete-time nonlinear systems under event-driven formulation,” IEEE Transactions on Automatic Control, vol. 65, no. 3, pp. 1272–1279, Mar. 2020.
[11]
[11] M. Ha, D. Wang, and D. Liu, “Event-triggered constrained control with DHP implementation for nonaffine discrete-time systems,” Information Sciences, vol. 519, pp. 110–123, 2020.
[12]
[12] L. Dong, X. Zhong, C. Sun, and H. He, “Adaptive event-triggered con- trol based on heuristic dynamic programming for nonlinear discrete-time systems,” IEEE Transactions on Neural Networks and Learning Systems, vol. 28, no. 7, pp. 1594–1605, Jul. 2017.
[13]
[13] D. Wang and D. Liu, “Learning and guaranteed cost control with event-based adaptive critic implementation,” IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 12, pp. 6004–6014, Dec. 2018.
[14]
[14] D. Wang, H. He, X. Zhong, and D. Liu, “Event-driven nonlinear discounted optimal regulation involving a power system application,” IEEE Transactions on Industrial Electronics, vol. 64, no. 10, pp. 8177–8186, Oct. 2017.
[15]
[15] H. Zhang, Y. Luo, and D. Liu, “Neural-network-based near-optimal control for a class of discrete-time affine nonlinear systems with control constraints,” IEEE Transactions on Neural Networks, vol. 20, no. 9, pp. 1490–1503, Sept. 2009.
[16]
[16] T. Meng and W. He, “Iterative learning control of a robotic arm experiment platform with input constraint,” IEEE Transactions on Industrial Electronics, vol. 65, no. 1, pp. 664–672, Jan. 2018.
[17]
[17] D. Wang, M. Zhao, and J. Qiao, “Intelligent optimal tracking with asymmetric constraints of a nonlinear wastewater treatment system,” International Journal of Robust and Nonlinear Control, vol. 31, no. 14, pp. 6773–6787, Sep. 2021.
[18]
[18] D. Wang, M. Zhao, M. Ha, and J. Ren, “Neural optimal tracking control of constrained nonaffine systems with a wastewater treatment application,” Neural Networks, vol. 143, pp. 121–132, 2021.
[19]
[19] S. E. Lyshevski, “Nonlinear discrete-time systems: constrained optimization and application of nonquadratic costs,” in Proceedings of the 1998 American Control Conference, vol. 6, pp. 3699–3703, 1998.
[20]
[20] Y. Zhang, B. Zhao, and D. Liu, “Deterministic policy gradient adaptive dynamic programming for model-free optimal control,” Neurocomputing, vol. 387, pp. 40–50, 2020.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICRAI '21: Proceedings of the 7th International Conference on Robotics and Artificial Intelligence
November 2021
135 pages
ISBN:9781450385855
DOI:10.1145/3505688
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 April 2022

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Constrained control
  2. event-triggered control
  3. iterative adaptive critic
  4. nonaffine systems
  5. nonzero-sum games
  6. optimal control.

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

ICRAI 2021

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 18
    Total Downloads
  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 08 Mar 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media