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Author:

Wang, Ding (Wang, Ding.) (Scholars:王鼎) | Ren, Jin (Ren, Jin.) | Ha, Mingming (Ha, Mingming.) | Qiao, Junfei (Qiao, Junfei.)

Indexed by:

EI Scopus SCIE

Abstract:

For discounted optimal regulation design, the stability of the controlled system is affected by the discount factor. If an inappropriate discount factor is employed, the optimal control policy might be unstabilizing. Therefore, in this article, the effect of the discount factor on the stabilization of control strategies is discussed. We develop the system stability criterion and the selection rules of the discount factor with respect to the linear quadratic regulator problem under the general discounted value iteration algorithm. Based on the monotonicity of the value function sequence, the method to judge the stability of the controlled system is established during the iteration process. In addition, once some stability conditions are satisfied at a certain iteration step, all control policies after this iteration step are stabilizing. Furthermore, combined with the undiscounted optimal control problem, the practical rule of how to select an appropriate discount factor is constructed. Finally, several simulation examples with physical backgrounds are conducted to demonstrate the present theoretical results.

Keyword:

Regulators Stability criteria reinforcement learning (RL) discount factor Costs Adaptive critic design optimal control Asymptotic stability stability Heuristic algorithms value iteration (VI) Optimal control linear quadratic regulator (LQR) Cost function

Author Community:

  • [ 1 ] [Wang, Ding]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing Lab Smart Environm Protect, Beijing 100124, Peoples R China
  • [ 2 ] [Ren, Jin]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing Lab Smart Environm Protect, Beijing 100124, Peoples R China
  • [ 3 ] [Qiao, Junfei]Beijing Univ Technol, Fac Informat Technol, Beijing Key Lab Computat Intelligence & Intellige, Beijing Lab Smart Environm Protect, Beijing 100124, Peoples R China
  • [ 4 ] [Wang, Ding]Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China
  • [ 5 ] [Ren, Jin]Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China
  • [ 6 ] [Qiao, Junfei]Beijing Univ Technol, Beijing Inst Artificial Intelligence, Beijing 100124, Peoples R China
  • [ 7 ] [Ha, Mingming]Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China

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Source :

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS

ISSN: 2162-237X

Year: 2022

Issue: 9

Volume: 34

Page: 6504-6514

1 0 . 4

JCR@2022

1 0 . 4 0 0

JCR@2022

ESI Discipline: COMPUTER SCIENCE;

ESI HC Threshold:46

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count: 47

SCOPUS Cited Count: 60

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 14

Affiliated Colleges:

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