Dynamic compensation of FOG navigation system based on particle swarm optimization and simulated annealing algorithm
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摘要: 光纤陀螺惯导系统在进行空间自主导航时，需要经历长期复杂的空间环境，这会使惯性仪表的某些性能发生变化，光纤陀螺仪的光功率下降是一种比较典型的失效模式，这会导致光纤陀螺仪的带宽下降，当航天器进行变轨或姿态机动时其导航精度会降低。针对上述问题，文中提出了微粒群优化的光纤陀螺仪动态补偿方法，根据光纤陀螺仪和参考模型在相同输入下的响应，优化得到补偿环节的参数。但微粒群算法存在过早陷入局部最优解的缺陷，为提高算法的全局搜索能力，采用模拟退火算法使其以较大的概率跳出局部最优解。通过光纤陀螺导航系统的动态导航试验验证了该方法能够有效地补偿光纤陀螺仪的动态特性，提高机动条件下的导航精度，具有较强的工程实用价值。Abstract: When spacecraft moves in the orbit using FOG navigation system, the performance of inertia instrument will fall off after experiencing a long and complicated environment. The power of light source falls off is a kind of fault mode. This mode will induce FOG's bandwidth to decline and the navigation precision will descend when spacecraft transfers to the other orbit or moves to a bigger angle. To resolve this problem, a method to compensate FOG's bandwidth using particle swarm optimization algorithm was brought forward. With this method a dynamic compensator could be realized without knowing the dynamic characteristics of FOG. The parameter of the compensator was optimized according to the measurement data of FOG and the reference model. But sometimes this method ran into local optimization easily. To increase this algorithm's performance, simulated annealing algorithm was induced to avoid local optimization. Finally, dynamic navigation experiment of FOG navigation system show that this algorithm is effective. This method can increase navigation precision when spacecraft moves to a bigger angle and possess a better engineering value.
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Key words:
- particle swarm algorithm /
- simulated annealing /
- dynamic compensation /
- FOG
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