Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

article · IEEE Transactions on Systems Man and Cybernetics Systems · 2019

Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control

Yuanheng Zhu, Dongbin Zhao, Haibo He

Cited by 43Open access

Abstract

For systems that can only be locally stabilized, control laws and their effective regions are both important. In this paper, invariant policy iteration is proposed to solve the optimal control of discrete-time systems. At each iteration, a given policy is evaluated in its invariantly admissible region, and a new policy and a new region are updated for the next iteration. Theoretical analysis shows the method is regionally convergent to the optimal value and the optimal policy. Combined with sum-of-squares polynomials, the method is able to achieve the near-optimal control of a class of discrete-time systems. An invariant adaptive dynamic programming algorithm is developed to extend the method to scenarios where system dynamics is not available. Online data are utilized to learn the near-optimal policy and the invariantly admissible region. Simulated experiments verify the effectiveness of our method.

Cite this paper

APA 7

Zhu, Y., Zhao, D., & He, H. (2019). Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control. IEEE Transactions on Systems Man and Cybernetics Systems, 50(11), 3959–3971. https://doi.org/10.1109/tsmc.2019.2911900

MLA 9

Zhu, Yuanheng, et al. “Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control.” IEEE Transactions on Systems Man and Cybernetics Systems, vol. 50, no. 11, 2019, pp. 3959–71, https://doi.org/10.1109/tsmc.2019.2911900.

Chicago

Zhu, Yuanheng, Dongbin Zhao, and Haibo He. 2019. “Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control.” IEEE Transactions on Systems Man and Cybernetics Systems 50 (11): 3959–71. https://doi.org/10.1109/tsmc.2019.2911900.

Harvard

Zhu, Y., Zhao, D. and He, H. (2019) ‘Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control’, IEEE Transactions on Systems Man and Cybernetics Systems, 50(11), pp. 3959–3971. Available at: https://doi.org/10.1109/tsmc.2019.2911900.

BibTeX
@article{zhu2019invariant,
  title = {{Invariant Adaptive Dynamic Programming for Discrete-Time Optimal Control}},
  author = {Zhu, Yuanheng and Zhao, Dongbin and He, Haibo},
  journal = {IEEE Transactions on Systems Man and Cybernetics Systems},
  volume = {50},
  number = {11},
  pages = {3959--3971},
  year = {2019},
  doi = {10.1109/tsmc.2019.2911900}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers