基于加权式多模型结构的歼击机自适应重构控制

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.

ADAPTIVE RECONFIGURATION CONTROL FOR FIGHTERS BASED ON WEIGHTED MULTIPLE-MODEL-STRUCTURE

Aimed at the complex flight control system of a fighter,a kind of robust adaptive control methods using multiple models is presented to make the control system track the given signal under different working conditions and to reconfigure the control law for some structural failures.Firstly,the multiple-model control structure is formed by several linear models and one fuzzy model.In the fuzzy logic way,weights of the multiple-model adaptive controller are obtained.Then,a dynamic structure adaptive neural network is introduced to stabilize the whole system and eliminate the influence caused by the frequent switching.Simulation results show that the control method is effective by demonstrating the normal flight process and the control simulation with failures.