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Related Experiment Video

Updated: Jan 2, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Model reference adaptive tracking control for hydraulic servo systems with nonlinear neural-networks.

Zhikai Yao1, Jianyong Yao1, Feiyu Yao1

  • 1School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China.

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|December 11, 2019
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Summary

This study introduces a novel control strategy using neural networks (NN) and robust integral of the sign of the error (RISE) feedback for hydraulic systems. The new composite controller enhances tracking performance by compensating for disturbances and achieving semi-global asymptotic stability.

Keywords:
Asymptotic stabilityHydraulic systemsModel referenceNeural networksRobust and adaptive control

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Area of Science:

  • Control Systems Engineering
  • Robotics
  • Fluid Power Systems

Background:

  • Hydraulic systems are prone to significant disturbances, including parametric uncertainties and external forces, which degrade performance.
  • High-performance tracking control is crucial for applications involving hydraulic actuation, but is often challenged by system nonlinearities and uncertainties.

Purpose of the Study:

  • To propose a composite nonlinear control design integrating neural networks (NN) and robust integral of the sign of the error (RISE) feedback for hydraulic systems.
  • To develop a novel NN-based feedforward component for compensating unknown state-dependent disturbances and improving online parameter adaptation.
  • To achieve semi-global asymptotic stability for the controlled hydraulic system without requiring acceleration measurements.

Main Methods:

  • A composite controller combining nonlinear neural networks (NN) and continuous robust integral of the sign of the error (RISE) feedback was designed.
  • A neural network feedforward component was incorporated for disturbance compensation and online input parameter updates.
  • A novel RISE term integrated with the NN feedforward component was developed to facilitate a model reference adaptive control structure.

Main Results:

  • The proposed controller demonstrated effective compensation for unknown state-dependent disturbances in hydraulic systems.
  • The controller achieved semi-global asymptotic stability for the controlled hydraulic system.
  • Experimental validation showed prescribed transient performance under rectangular trajectories and steady-state performance under sinusoidal trajectories.

Conclusions:

  • The composite NN-RISE controller offers a robust and effective solution for high-performance tracking control of hydraulic systems.
  • The integration of NN feedforward with RISE feedback provides enhanced disturbance rejection and stability guarantees.
  • The developed control strategy advances the state-of-the-art in adaptive and robust control for fluid power applications.