|Research on UUV Recovery Active Disturbance Rejection Control Based on LMNN Compensation
Xue Du, Wenhua Wu, Wei Zhang*, and Shouyi Hu
International Journal of Control, Automation, and Systems, vol. 19, no. 7, pp.2569-2582, 2021
Abstract : As a kind of intelligent marine equipment, its successful recovery is the basis of Unmanned Underwater Vehicle (UUV)’s normal working and completing the mission successfully. However, the mathematical model of UUV is severely coupled and highly nonlinear, and may be subject to complex interference in the recovery process. Besides, the model could not be determined completely. Active disturbance rejection control (ADRC) method does not need the beforehand information of the unknown disturbance and also can ensure the stability. But conventional ADRC method with fixed parameters could not adjust to UUV complicated motion control. This paper introduces the adaptive wavelet neural network optimized by Levenberg-Marquardt algorithm, and puts forward a novel ADRC control method improved by wavelet neural network algorithm and Levenberg-Marquardt algorithm, for partial system identification and uncertain model compensation. Moreover, with pitching moment change considered in the process of UUV recovery, two dimensionless hydrodynamic coefficients are defined based on near-wall effect. The simulation experiments have been tested to verify the effectiveness of the proposed control. The results indicate that the ADRC with Levenberg-Marquardt neural network could control UUV recovery process in the variable disturbance environment more stable and reduce the ADRC computational burden.
Active disturbance rejection control (ADRC), neural network compensation, underwater recovery control, unmanned underwater vehicles (UUV).
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