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Related Experiment Video

Updated: Nov 30, 2025

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

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Published on: April 4, 2017

Improved generalized proportional integral observer based control for systems with multi-uncertainties.

Jian Feng¹, Bingkuan Yin¹

¹School of Information Science and Engineering, Northeastern University, Shenyang 110819, China.

ISA Transactions

|November 16, 2020

Summary

This summary is machine-generated.

This study introduces an improved generalized proportional integral observer (IGPIO) and IGPIO-based control (IGPIOBC) strategy to effectively manage systems with multiple uncertainties. The novel approach enhances control accuracy and system stability for complex applications.

Keywords:

Generalized proportional integral observer based control Multi-uncertainties Observer gains Singular perturbation approach

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Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

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Published on: November 24, 2021

Area of Science:

Control Systems Engineering
Nonlinear Control Theory
Observer Design

Background:

Traditional Active Disturbance Rejection Control (ADRC) faces challenges with multi-uncertainties due to mismatched conditions and non-integral-chain forms.
The stability guarantees of traditional Extended State Observers (ESO) may not ensure sufficient observation accuracy for complex systems.

Purpose of the Study:

To develop an advanced observer for accurate estimation of multi-uncertainties and their derivatives.
To propose a novel control strategy that actively and precisely eliminates these multi-uncertainties.
To provide theoretical stability proofs and analyze the relationship between observer parameters and performance.

Main Methods:

Introduction of an Improved Generalized Proportional Integral Observer (IGPIO) for enhanced uncertainty estimation.
Development of an IGPIO-based control (IGPIOBC) strategy for active uncertainty elimination.
Application of singular perturbation approach and Lyapunov theory for bounded stability analysis of the observer and closed-loop system.

Main Results:

The proposed IGPIO accurately estimates multi-uncertainties and system derivatives.
The IGPIOBC strategy effectively eliminates multi-uncertainties, demonstrating improved control performance.
Theoretical analysis confirms the bounded stability of the observer and the overall control system.
The relationship between IGPIO gain parameters and its bandwidth is clearly deduced.

Conclusions:

The developed IGPIO and IGPIOBC strategy offer a robust solution for controlling systems with multi-uncertainties.
Simulation results on numerical, RLC circuit, and DC motor systems validate the proposed method's effectiveness and accuracy.
The approach enhances control system performance in the presence of significant and complex uncertainties.