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首页> 外文期刊>The Aeronautical Journal >An optimal-fuzzy two-phase CLOS guidance law design using ant colony optimisation
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An optimal-fuzzy two-phase CLOS guidance law design using ant colony optimisation

机译：基于蚁群优化的最优模糊两阶段CLOS制导律设计

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摘要

The well-known ant colony optimisation (ACO) meta-heuristic is applied to optimise the parameters of a new fuzzy command to line-of-sight (CLOS) guidance law. The new guidance scheme includes two phases, a midcourse and a terminal phase. In the first phase, a lead strategy is utilised which reduces the acceleration demands. A proportional derivative (PD) fuzzy sliding mode controller is used as the main tracking controller of the first phase. Moreover, a supervisory controller is coupled with the main tracking controller to guarantee the missile flight within the beam. In the terminal phase, a pure CLOS guidance law without lead angle is utilised. For this phase, a new hybrid fuzzy proportional-integral-derivative (PID) fuzzy sliding mode controller is proposed as a high precision tracking controller. The parameters of the proposed controllers for the first and the second phases are optimised using ACO. In this regard, the recently developed continuous ant colony system (CACS) algorithm is extended to multi-objective optimisation problems and utilised to optimise the parameters of the pre-constructed fuzzy controllers. The performance of the resulting guidance law is evaluated at different engagement scenarios and compared with the well-known feedback linearisation method. The comparison is also made in the presence of measurement noise.
机译：应用著名的蚁群优化（ACO）元启发式算法优化对视线（CLOS）制导律的新模糊命令的参数。新的指导方案包括两个阶段，中间阶段和结束阶段。在第一阶段，采用领先策略来减少加速需求。比例微分（PD）模糊滑模控制器用作第一阶段的主跟踪控制器。此外，监督控制器与主跟踪控制器耦合以确保导弹在波束内飞行。在末期阶段，将采用无超前角的纯CLOS制导律。在这一阶段，提出了一种新型的混合模糊比例积分微分（PID）模糊滑模控制器作为高精度跟踪控制器。使用ACO对建议的第一阶段和第二阶段控制器的参数进行了优化。在这方面，最近开发的连续蚁群系统（CACS）算法被扩展到多目标优化问题，并被用来优化预先构造的模糊控制器的参数。在不同的参与场景下评估得出的制导律的性能，并与众所周知的反馈线性化方法进行比较。在存在测量噪声的情况下也进行比较。

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