Abstract
In this paper, controllable pitch propeller (CPP) has been used to improve the maneuvering at a fixed shaft speed. The proportional-derivative (PD) control method has been applied to obtain high efficiency by changing the pitch angle. The controller results have been evaluated and learned by a fast backpropa-gation algorithm (FBA). The neural network results show that learning of pitch behavior has been verified, and the FBA performance of CPP controller is better than that of the PD controller.
Keywords
Backpropagation
Propeller
Controller (irrigation)
Blade pitch
Control theory (sociology)
Artificial neural network
Pitch angle
Pitch control
PID controller
Engineering
Control (management)
Computer science
Algorithm
Control engineering
Artificial intelligence
Mechanical engineering
Marine engineering
Physics
Rotor (electric)
Subject Areas
Cavitation Phenomena in Pumps
·Mechanics of Materials ·Physical Sciences
Real-time simulation and control systems
·Control and Systems Engineering ·Physical Sciences
Advanced Control Systems Optimization
·Control and Systems Engineering ·Physical Sciences
Citations by Year
2014: 1
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