轻小型多旋翼无人机云台是一种复杂机电伺服系统, 要求兼具轻质量与快响应等机电特性。本文针对传统方法在机电伺服系统中设计的不足, 以轻小型多旋翼无人机云台为研究对象, 提出一种针对系统带宽的机电多目标优化设计方法。方法中, 系统结构部分通过灵敏度分析得到7个尺寸设计参数, 并以一阶模态和质量为目标进行优化; 系统控制部分以速率环和位置环控制器参数为设计变量, 并以上升时间、调节时间和绝对积分误差(Integral Absolute Error, IAE)为目标进行优化。在优化设计中, 将近似模型与多目标遗传算法相结合, 以降低优化复杂度、并提高优化效率及全局寻优能力。对方法进行仿真分析, 结果表明: 相比初始结构系统和控制系统模型, 采用机电多目标优化设计方法后, 结构部分质量降低了8.8%, 控制部分IAE型积分误差、调节时间及上升时间等主要性能参数分别降低了54.8%、81.9%和53.4%。最后采用锤击法对云台结构进行模态实验, 实验得到的一阶模态频率与优化结果的误差为13.4%。说明提出方法可有效实现云台系统机电总体多目标优化。

The light and small pan-tilt system of a multi-rotor unmanned aerial vehicle is a complicated electromechanical servo system that requires a number of desirable properties such as light weight and rapid response to be realized. We focus on the inherent limitations of the traditional methods in the electromechanical servo-system design to present a multi-objective optimization method for a mechatronic system based on the bandwidth. For the structure system, seven-dimensional parameters were selected using sensitivity analysis in which the mass and first-order natural frequency are considered as the optimization goals. For the control system, the controller parameters in the rate and position loops are selected as design variables in which the rise time, regulating time, and integral absolute error (IAE) are considered as the optimization goals. In the optimization process, an optimization method that combines the approximation model and multi-objective genetic algorithm is proposed to reduce the complexity, improve the efficiency, and improve the overall optimization ability during the optimization process. Simulations are then conducted to verify the proposed method. The results show that, compared with the original model of the control and structure systems, the mass, IAE, regulating time, and rise time are reduced by 8.8%, 54.8%, 81.9%, and 53.4%, respectively. Finally, a modal pan-tilt experiment is carried out by hammering, and the error in the experimental and optimization results is found to be 13.4%. Therefore, the optimization method is effective.