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针对复杂的歼击机飞控系统,提出一种基于多模型结构的鲁棒自适应控制方法,使得系统可以在不同的运行环境下跟踪给定的信号,并且对飞机操纵面故障具有重构作用。首先,由多个线性模型和一个模糊模型构成多模型控制结构,采用模糊方法设计多模型自适应控制器中的权值系数,再引入动态结构自适应神经网络以保证系统的稳定性,故避免了模型切换引起的噪声。最后,对歼击机进行正常和故障状态下的控制仿真,结果验证了所提控制方法的有效性。
Aiming at the complex fighter flight control system, a robust adaptive control method based on multi-model structure is proposed, which can make the system track a given signal under different operating conditions and reconstruct the control plane faults. First of all, a multi-model control structure is composed of a number of linear models and a fuzzy model. The fuzzy coefficient is used to design the weight coefficient of the multi-model adaptive controller, and then the dynamic structure adaptive neural network is introduced to ensure the stability of the system. The noise caused by the model switching. Finally, the control simulation of the fighter plane under normal and fault conditions is carried out. The results verify the effectiveness of the proposed control method.