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The paper proposes optimal placement methods for MFC actuators and sensors in active vibration control of aero-engine blades using Particle Swarm Optimization and Differential Evolution algorithms.

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System
MFC

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Abstract

Sensors and actuators placements play an important role in the control performance of an active vibration control system for piezoelectric smart aero-engine blades. Incorrect placement of sensors and actuators may lead to instability in the control system. This paper proposes optimal placement methods based on the Particle Swarm Optimization (PSO) algorithm for actuators and sensors. Firstly, three sensors and actuators placement optimization schemes are proposed based on the modal analysis and transient analysis results of ANSYS. These schemes include the superposition of non-absolute normalized modal strains, the energy criterion for transient analysis, and the superposition of absolute normalized modal strains. Secondly, it is ensured that the placements of the MFC piezoelectric elements are optimized based on the Particle Swarm Optimization (PSO) Algorithm and Differential Evolution (DE) Algorithm within the boundary constraints. Finally, the convergence of the fitness function based on the PSO algorithm and the DE algorithm as well as the three schemes are comparatively analyzed and the optimal placement of the MFC is found. Simulation results show that the last scheme optimized based on the PSO algorithm has better convergence effect and can obtain the optimal placements of sensors and actuators.

Keywords

ActuatorAero engineVibrationAutomotive engineeringActive vibration controlVibration control

Identifiers

DOI
10.23919/CCC63176.2024.10662223
Journal
2024 43rd Chinese Control Conference (CCC)
Year
2024