Empirical Modeling of 2-Degree-of-Freedom Azimuth Underwater Thruster Using a Signal Compression Method

This paper presents an empirical modeling of a 2-Degree-of-Freedom (DoF) azimuth thruster using the signal compression method. The thruster has a gimbal mechanism with two servo motors and generates thrust in arbitrary directions. This mechanism can reduce the number of thrusters in an underwater robot and contribute to compact design. When an underwater robot is controlled with azimuth thrusters, the influence from the rotational motion of the thruster has to be considered, and a dynamic model of the azimuth thruster is needed. It is difficult to derive an analytical model because the system model depends on complicated fluid dynamics. In this study, empirical models of force and moment for rotational motion were derived for practical use through frequency analysis. A signal compression method can effectively extract the system model in the frequency domain from just the mechanically constrained frequency response. Experiments were carried out using a force/torque sensor that was connected to a cantilever in a water tank. The system model was analyzed with Bode plots, and the model coefficients were derived through curve fitting. The derived model was verified by a validation experiment.

Step Respons Motor DC by Using Compression Signal Method

Output signal in the form of a step response of a DC motor can be obtained by providing the input signal to the motor in the form of a signal step directly. Step response obtained in this way usually contains a lot of noise. To reduce noise, this research was designed with the aim to get the step response using signal compression method in which the input signal is not a step but a signal with a specific shape given to the motor and if the output signal of the motor is compressed, it will obtain impulse response. Step response of the DCmotor can be obtained by doing the integral to the impulse response. Step response which is obtained using signal compression method will be used to estimate parameters model of DC motor to see the validity of this method. The result of this research shows that the estimated value of the parameters from the step response has value closer to the value of the parameters given to the model of a DC motor. The conclusion of this research is the method of signal compression can be used to obtain the step response of a DC motor model. Further research will be conducted on the actual motor instead of using a mathematical model.