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首页> 外文期刊>Journal of aerospace engineering >Nonlinear FOPID and Active Disturbance Rejection Hypersonic Vehicle Control Based on DEM Biogeography-Based Optimization
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Nonlinear FOPID and Active Disturbance Rejection Hypersonic Vehicle Control Based on DEM Biogeography-Based Optimization

机译：基于DEM生物地理学的非线性FOPID和主动干扰抑制超音速飞行器控制

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摘要

This paper proposes an accurate system model independent resilient control approach with heuristic parameter optimization algorithm for air-breathing hypersonic vehicle tracking control. The control action is generated by the combination of nonlinear fractional-order proportional-integral-derivative (FOPID) and the active disturbance rejection control (ADRC). In particular, the FOPID controller increases two-degree-of-freedom variables, which improves the precision and stability of the control effect. The ADRC controller possesses aspects of the assimilation characteristics of the modern control theory and does not rely on the accurate mathematical model function, which is very suitable for a hypersonic vehicle system with parameter uncertainties and disturbances. Meanwhile, a new differential evolution exponential-cosine mixed migration (DEM) strategy for determining the biogeography-based optimization (BBO) migration rate to improve the optimization algorithm is proposed, which is mainly used for calculating tuning parameters of the FOPID ADRC. The improved hybrid algorithm is verified versus 14 benchmark functions and the practical optimization problems of the hypersonic vehicle vertical FOPID ADRC system are verified to illustrate the improved performance with the proposed approach. The effectiveness and robustness of the proposed method was verified by the simulation results. (C) 2017 American Society of Civil Engineers.
机译：提出了一种基于启发式参数优化算法的精确系统模型独立弹性控制方法，用于呼吸高超音速飞行器的跟踪控制。通过非线性分数阶比例积分微分（FOPID）和有源干扰抑制控制（ADRC）的组合来产生控制作用。尤其是，FOPID控制器增加了两个自由度变量，从而提高了控制效果的精度和稳定性。 ADRC控制器具有现代控制理论的同化特性，并且不依赖精确的数学模型函数，非常适合参数不确定和干扰的高超声速车辆系统。同时，提出了一种新的差分进化指数-余弦混合迁移（DEM）策略，用于确定基于生物地理的优化（BBO）迁移率，以提高优化算法，该策略主要用于计算FOPID ADRC的调整参数。针对14种基准函数对改进的混合算法进行了验证，并验证了高超声速车辆垂直FOPID ADRC系统的实际优化问题，以说明所提出方法的改进性能。仿真结果验证了该方法的有效性和鲁棒性。 （C）2017年美国土木工程师学会。

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