基于多目标粒子群优化算法的全电式高平机轨迹优化OA
Trajectory Optimization of Fully Electric Elevating Equilibrator Based on Multi-Objective Particle Swarm Optimization Algorithm
针对传统气液式高平机可靠性低、响应速度慢等技术瓶颈,使用电动缸驱动的全电式高平机取代传统气液式高平机,实现毫秒级快速响应.构建了自行火炮起落部分数学模型,计算获得全电式高平机起落过程的力矩平衡与运动轨迹特性.利用多目标粒子群优化(Multi-Objective Particle Swarm Optimization,MOPSO)算法对制约起落性能的核心参数实施优化重构,显著增强了起落过程动态性能,为实现自行火炮全电化提供了重要理论支撑.
Aiming to address the technical limitations of traditional pneumatic-hydraulic elevating equilibrator,such as low reliability and slow response speed,a fully electric elevating equilibrator driven by an electric cylinder is developed to replace its traditional counterpart,achieving millisecond-level rapid response.A mathematical model of the self-propelled artillery's elevating equilibrator is constructed to analyze the torque balance and motion trajectory characteris-tics during the elevation process of the all-electric mechanism.A multi-objective particle swarm optimization algorithm is employed to optimize and reconfigure the core parameters affecting elevation performance,leading to a significant en-hancement in the dynamic performance of the elevation process.It provides important theoretical support for the full electrification of self-propelled artillery.
王子攸;葛建立;张杰;杨国来;王修业
南京理工大学机械工程学院,江苏 南京 210094南京理工大学机械工程学院,江苏 南京 210094内蒙古北方重工业集团有限公司装备研究所,内蒙古 包头 014033南京理工大学机械工程学院,江苏 南京 210094南京理工大学机械工程学院,江苏 南京 210094
军事科技
全电式高平机火炮调炮多目标粒子群优化算法运动轨迹优化
electric elevating equilibratorartillery adjustmentmulti-objective particle swarm optimizationmotion tra-jectory optimization
《海军航空大学学报》 2026 (2)
401-407,418,8
国家自然科学基金(52475020)
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