자기 회귀 웨이블릿 신경 회로망을 이용한 자율 수중 운동체의 방향 제어에 관한 연구 = A Study on Steering Control of Autonomous Underwater Vehicle Using Self-Recurrent Wavelet Neural Network

다국어 초록 (Multilingual Abstract)

In this paper, we propose a new method for designing the steering controller of autonomous underwater vehicle(AUV) using a self-recurrent wavelet neural network(SRWNN). The proposed control method is based on a direct adaptive control technique, and a SRWNN is used for the controller of horizontal motion of a AUV. A SRWNN　is tuned to minimize errors between the SRWNN outputs and the outputs of AUV via the gradient descent(GD) method. Through the computer simulations, we compare the performance of the propose controller with that of the MLP based controller to verify and effectiveness of the propose controller. The results obtained from simulations are summarized as follows:

1) From the simulation results, it is shown that the SRWNN based controller is stable and has faster convergence than the MLP based controller.

2) It is shown that the MSEs of the MLP based controller and the SRWNN based controller are 0.0028, and 0.0019, respectively. From the results of MSE, it is shown that the SRWNN based controller has the least error.