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Optimization, Test and Diagnostics of Miniaturized Hall Thrusters
12:22

Optimization, Test and Diagnostics of Miniaturized Hall Thrusters

Published on: February 16, 2019

Strong stabilization servo controller with optimization of performance criteria.

Andrej Sarjaš1, Rajko Svečko, Amor Chowdhury

  • 1FERI, Univerza v Mariboru, Smetanova 17, 2000 Maribor, Slovenia. andrej.sarjas@uni-mb.si

ISA Transactions
|April 20, 2011
PubMed
Summary
This summary is machine-generated.

A robust controller was synthesized for servo mechanisms using pole placement and H(∞) metrics. This method ensures stability and robustness for Brushless DC (BLDC) and Brush DC (BDC) motors, validated by genetic algorithms.

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A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
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Area of Science:

  • Control Systems Engineering
  • Robotics
  • Electrical Engineering

Background:

  • Servo mechanisms require precise control for optimal performance.
  • Brushless DC (BLDC) and Brush DC (BDC) motors are widely used in various applications.
  • Ensuring robustness and stability in control systems is critical, especially under varying conditions.

Purpose of the Study:

  • To synthesize a simple, robust controller for servo mechanisms.
  • To utilize pole placement techniques and H(∞) metrics for controller design.
  • To ensure the stability and robustness of closed-loop systems with BLDC and BDC motors.

Main Methods:

  • Pole placement technique combined with H(∞) metrics for controller synthesis.
  • Solving polynomial equations using Manabe standard polynomial form and parametric solutions.
  • Robustness assessment using uncertainty models and the H(∞) norm.
  • Optimization using a genetic algorithm, specifically Differential Evolution (DE).
  • Stability verification using Šiljak's absolute stability test and Lipatov's stability condition.

Main Results:

  • A robust servo controller structure was successfully designed and optimized.
  • The controller demonstrated robustness against system uncertainties.
  • The DE optimization effectively determined suboptimal solutions for the controller.
  • Šiljak's test and Lipatov's condition confirmed the stability and robustness characteristics.

Conclusions:

  • The proposed method provides a simple and robust controller for servo mechanisms.
  • The integration of pole placement, H(∞) metrics, and DE optimization is effective.
  • The polynomial-based stability tests are suitable for automated control design and optimization.