XYXinlu Yu

Xinlu Yu

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

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Xinlu Yu has a total of 6 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Generalized High-Order LADRC Tracking Control for VICTS Hollow Annular Direct-Drive Motor Considering Non-Stationary Disturbances

    by Xinlu Yu, Jiacheng Lu, Ping Gao, Pingfa Feng, Lin Jia

    This paper proposes a generalized high-order linear active disturbance rejection control (GHO-LADRC) method to suppress non-stationary disturbances in VICTS antenna direct-drive motors during high-dynamic scanning. First, a fourth-order generalized extended state observer is constructed, in which the derivative of the total disturbance is explicitly modeled as an extended state. This configuration enables real-time observation of the disturbance rate of change and suppresses the phase lag inherent in traditional ADRC during rapid disturbance variations through disturbance feedforward compensation. Secondly, drawing on singular perturbation theory and the motor’s dual-time-scale characteristics, this work precisely decouples and explicitly extracts the nonlinear friction and electromagnetic damping terms during the modeling stage. By integrating the extracted electromagnetic damping terms and the disturbance variation rate, an improved model-assisted control law is formulated, enabling active compensation for intense dynamic interference. Theoretical analysis and experimental results demonstrate that the proposed method significantly enhances disturbance rejection capability and satellite communication accuracy. As the first application of GHO-LADRC in the field of direct-drive VICTS antenna control, this work validates its effectiveness in improving system robustness within complex dynamic environments.

  • Open Access

    Vibration Suppression and Dynamic Optimization of Multi-Layer Motors for Direct-Drive VICTS Antennas

    by Xinlu Yu, Aojun Li, Pingfa Feng, Jianghong Yu

    Weight reduction and dynamic performance optimization are critical for airborne direct-drive VICTS satellite communication antennas, which require lightweight, high-speed, and high-precision rotation. Traditional vibration suppression methods, such as uniform support layout and added damping, rely heavily on empirical trial and error, lack targeted modal control, and cannot balance lightweight design with dynamic stiffness. To address these issues, this paper proposes a wave-theory-based dynamic modeling and rapid optimization method for multi-layer rotating components in direct-drive VICTS antennas. The kinematic model of the rotating ring and ball revolution excitation are derived using the annular wave equation and bearing kinematics. A Modal Blocking Mechanism is established: placing support balls at positions satisfying the half-wavelength constraint suppresses target mode shapes via wave interference, achieving vibration attenuation at the source. A homogenization equivalent method based on RVE is developed for irregular cross-section rings, yielding analytical expressions for in-plane equivalent elastic modulus and out-of-plane equivalent shear modulus. These parameters are integrated into the wave equation to analytically solve vibration modes, avoiding iterative finite element computations. A rapid multi-objective optimization framework is then constructed, minimizing the structural weight and maximizing the modal separation interval under dynamic stiffness and excitation frequency constraints. Numerical simulations, FE analysis, and prototype tests validate the method: the maximum analytical error is only 3.1%. Compared with uniform support designs, the optimized structure achieves a 40% weight reduction, a 40% increase in minimum modal separation, and a 65% reduction in the RMS tracking error. This work provides an efficient, deterministic dynamic design method for large-diameter ring structures, transforming vibration control from empirical adjustment into a precise, physics-informed optimization.