Eugenio Martin Gelos;Marcos Gabriel Judewicz;Marcos Alan Funes;Daniel Oscar Carrica
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引用次数: 0
Abstract
This work presents a novel circuit analogy for modeling and controlling mechanical motion rectifier (MMR)-based power take-off (PTO) systems in wave energy applications. Each component of the MMR is individually modeled, with particular emphasis on their velocity and torque constraints to derive their electrical analogies. The overall MMR circuit is synthesized using basic kinematic constraints, and a comprehensive friction model is integrated to address the limitations of existing approaches. The proposed circuit model facilitates the derivation of explicit expressions characterizing the MMR's nonlinear dynamics. A specific identification procedure is employed to determine the circuit parameters of an MMR prototype, which is subsequently validated through experimental testing. The developed electrical analogy offers a generalized modeling approach for MMR-based devices, allowing seamless adaptability to various MMR wave energy converters (WECs) and rectification mechanisms. This, along with the integrated friction model, explicit expressions for nonlinearities, and proven experimental accuracy, establishes a robust framework for developing comprehensive wave-to-wire models of different MMR-based WECs. Additionally, the inherited electrical simulation environment is particularly well suited for designing control techniques on the generation side aimed at maximizing wave energy absorption.
期刊介绍:
Journal Name: IEEE Transactions on Industrial Electronics
Publication Frequency: Monthly
Scope:
The scope of IEEE Transactions on Industrial Electronics encompasses the following areas:
Applications of electronics, controls, and communications in industrial and manufacturing systems and processes.
Power electronics and drive control techniques.
System control and signal processing.
Fault detection and diagnosis.
Power systems.
Instrumentation, measurement, and testing.
Modeling and simulation.
Motion control.
Robotics.
Sensors and actuators.
Implementation of neural networks, fuzzy logic, and artificial intelligence in industrial systems.
Factory automation.
Communication and computer networks.