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基于粒子群自适应差分进化算法的动压缸电液伺服系统辨识
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Identification of Dynamic Pressure Cylinder Electro-hydraulic Servo System Based on Particle Swarm Adaptive Differential Evolution Algorithm
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    摘要:

    给出了轨道路基测试装置动压缸电液伺服系统AMESim模型和传递函数。针对标准差分进化算法早熟和自适应差分进化算法收敛慢的问题,结合粒子群算法收敛快的优点,构造了一种以粒子群为外环、自适应差分进化为内环的辨识算法。设计该系统辨识数据采集方案,得到其AMESim模型的响应数据,开展PSOADE辨识仿真和对比分析,结果表明:PSOADE不仅精度高、同一性好,而且迭代快、易收敛。最后得到了基于PSOADE算法辨识参数的动压缸电液伺服系统参数模型,仿真验证了该模型的有效性。

    Abstract:

    The dynamic pressure cylinder electro-hydraulic servo system AMESim model and transfer function are provided. Aiming at the problem that the standard differential evolution algorithm premature and adaptive differential evolution algorithm converge slowly, combined with the advantage of fast convergence of particle swarm optimization algorithm(PSOA), an identification algorithm was constructed based on particle swarm as outer loop and adaptive differential evolution algorithm as inner loop. The system identification data acquisition scheme was designed and the response data of its AMESim model was obtained, and the PSOADE algorithm identification simulation and comparative analysis were carried out. The results show that PSOADE algorithm not only has high precision and good identity, but also fast to iterate and easy to converge. Finally, the parameter model of the dynamic pressure cylinder electro-hydraulic servo system is obtained based on PSOADE algorithm, and the validity of the model is proved by simulation.

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邓攀,刘洋,李华,胡念慈,李恒山.基于粒子群自适应差分进化算法的动压缸电液伺服系统辨识[J].机床与液压,2019,47(23):169-173.
. Identification of Dynamic Pressure Cylinder Electro-hydraulic Servo System Based on Particle Swarm Adaptive Differential Evolution Algorithm[J]. Machine Tool & Hydraulics,2019,47(23):169-173

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  • 在线发布日期: 2020-03-12
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