Cruise Speed Estimation Strategy Based On Multiple Fuzzy Logic And Extended State Observer For Low-Cost Auv

This article presents an effective cruise speed estimation strategy for low-cost autonomous underwater vehicles under the impact of complex ocean currents and the absence of critical navigation sensors. The estimation strategy is based on the motor feedback information, including motor current and propeller speed. The cruise speed estimation strategy requires a rough speed estimation and minor adjustments to ensure that the estimated speed is valuable. In this article, the multiple fuzzy logic is applied to generate the mapping between the motor current deviation, propeller speed, and cruise speed deviation. Afterward, recursive least square is introduced to fine-tune the rough speed based on the reference propeller torque estimated by extended state observer. The experimental results demonstrate that the estimated speed of the proposed method can reach, on average, 96% of the Doppler velocity log measurement accuracy under the ocean currents conditions. The experimental results also illustrate that the method proposed in this article has strong robustness.