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Adaptive fuzzy prescribed time tracking control for nonlinear systems with input saturation.

Haixiu Xie1, Yuanwei Jing1, Georgi M Dimirovski2

  • 1College of Information Science and Engineering, Northeastern University, Shenyang 110819, Liaoning, China.

ISA Transactions
|October 6, 2023
PubMed
Summary

This study introduces adaptive fuzzy control for strict-feedback systems, ensuring user-defined tracking performance despite input saturation and disturbances. The novel approach guarantees convergence within a prescribed time, enhancing control reliability.

Keywords:
Funnel controlInput saturationNonlinear systemsPractically prescribed time tracking

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Area of Science:

  • Control Engineering
  • Fuzzy Systems
  • Nonlinear Control Theory

Background:

  • Strict-feedback systems present challenges in control design due to inherent nonlinearities.
  • Input saturation and external disturbances degrade control performance and system stability.
  • Prescribed-time control aims for faster convergence than traditional finite-time methods.

Purpose of the Study:

  • To develop an adaptive fuzzy prescribed-time tracking control strategy for strict-feedback systems.
  • To address asymmetric tracking performance, input saturation, and external disturbances simultaneously.
  • To ensure reliable control implementation and pre-specified tracking behavior.

Main Methods:

  • Construction of a saturation-based fixed-time funnel boundary using modification signals.
  • Recasting bounded tracking errors into a new variable with zero initial value using a fixed-time tracking performance function.
  • Utilizing auxiliary systems for modification signal generation and compensation of input saturation effects.
  • Employing backstepping design with fuzzy approximation for control synthesis.

Main Results:

  • The proposed funnel boundary adapts to input saturation, mitigating singularity risks.
  • Tracking error behavior is pre-specified over a finite time, independent of initial conditions.
  • The adaptive fuzzy controller ensures tracking error convergence to a user-defined region within a prescribed time.
  • Control is achieved without relying on fractional power feedback of system states.

Conclusions:

  • The developed adaptive fuzzy control approach effectively handles complex dynamics in strict-feedback systems.
  • The method provides guaranteed prescribed-time convergence and robust performance against saturation and disturbances.
  • Simulation examples validate the feasibility and effectiveness of the proposed control strategy.