Event-triggered constrained control using explainable global dual heuristic programming for nonlinear discrete-time systems

Journal Article (2022)
Author(s)

Bo Sun (TU Delft - Aerospace Engineering)

Erik Jan van Kampen (TU Delft - Aerospace Engineering)

Research Group
Control & Simulation
DOI related publication
https://doi.org/10.1016/j.neucom.2021.10.046 Final published version
More Info
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Publication Year
2022
Language
English
Research Group
Control & Simulation
Volume number
468
Pages (from-to)
452-463
Downloads counter
216
Collections
Institutional Repository
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Abstract

This paper develops an event-triggered optimal control method that can deal with asymmetric input constraints for nonlinear discrete-time systems. The implementation is based on an explainable global dual heuristic programming (XGDHP) technique. Different from traditional GDHP, the required derivatives of cost function in the proposed method are computed by explicit analytical calculations, which makes XGDHP more explainable. Besides, the challenge caused by the input constraints is overcome by the combination of a piece-wise utility function and a bounding layer of the actor network. Furthermore, an event-triggered mechanism is introduced to decrease the amount of computation, and the stability analysis is provided with fewer assumptions compared to most existing studies that investigate event-triggered discrete-time control using adaptive dynamic programming. Two simulation studies are carried out to demonstrate the applicability of the constructed approach. The results present that the developed event-triggered XGDHP algorithm can substantially save the computational load, while maintain comparable performance with the time-based approach.