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Event-triggered adaptive optimal tracking control for nonlinear stochastic systems with dynamic state constraints.

Yan Wei1, Xinyi Yu1, Yu Feng1

  • 1College of Information Engineering, Zhejiang University of Technology, Hangzhou 30032, China.

ISA Transactions
|April 19, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces an adaptive optimal tracking control method for uncertain nonlinear systems. The event-triggered approach ensures system robustness and avoids Zeno behavior in stochastic systems.

Keywords:
Adaptive dynamic programmingEvent-triggered controlNonlinear mappingState constraintsStochastic systems

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Area of Science:

  • Control Theory
  • Nonlinear Systems
  • Stochastic Processes

Background:

  • Dynamic state constraints pose challenges in nonlinear system control.
  • Stochastic disturbances degrade system performance and stability.
  • Existing control methods may not effectively handle both constraints and disturbances simultaneously.

Purpose of the Study:

  • To develop an event-triggered adaptive optimal tracking control strategy.
  • To address uncertain nonlinear systems with stochastic disturbances and dynamic state constraints.
  • To ensure system robustness and bounded errors.

Main Methods:

  • A novel unified tangent-type nonlinear mapping function for dynamic state constraints.
  • A neural networks (NNs)-based identifier for stochastic disturbances.
  • Adaptive dynamic programming (ADP) with an identifier-actor-critic architecture.
  • An event-triggering mechanism to optimize control actions.

Main Results:

  • The proposed event-triggered adaptive optimal control (ETC) approach is first presented.
  • Guaranteed robustness for stochastic systems.
  • Semi-globally uniformly ultimately bounded (SGUUB) in the mean square of NNs adaptive estimation error.
  • Avoidance of Zeno behavior.

Conclusions:

  • The developed ETC approach effectively manages uncertain nonlinear systems with stochastic disturbances and dynamic state constraints.
  • The method ensures system stability and performance while optimizing control.
  • Simulation results validate the proposed control strategy's effectiveness.