液压飞行仿真转台外框FNN控制器设计及仿真

以液压转台外框为控制对象,根据模糊控制理论,设计出直接自适应模糊控制器(DAFC,Direct Adaptive Fuzzy Controller)和同步模糊控制器(SFC,Synchronizing Fuzzy Controller)来解决外框负载干扰和双液压马达同步驱动这2个影响转台控制性能的主要问题;其中直接自适应模糊控制器还与PID控制器一起组成并行控制系统来抑制系统静态误差和动态干扰.针对模糊控制器自学习能力较差等缺陷,在模糊控制的基础上,根据模糊神经网络(FNN,Fuzzy Neural Net)模型设计出多输入多输出(MIMO,Multi-Input Multi-Output)的FNN控制器.软件仿真结果表明,当转台外框负载发生变化或外框两马达转速相差较大时,使用FNN模型的智能控制系统仍具有较高的位置跟踪精度和动态性能.

Hydraulic simulator outer gimbal FNN controller design and simulation

Taking hydraulic simulator outer gimbal as controlled object, direct adaptive fuzzy controller(DAFC) and synchronizing fuzzy controller(SFC) for outer gimbal to resolve disturbance from load and synchronizing drive of dual hydraulic motors, which are primary factors affected on the performance of hydraulic simulator outer gimbal, were presented, based on employing fuzzy control theory. Adaptive fuzzy controller was combined with PID controller to compose parallel control system, which was aimed at reducing static error and suppressing dynamic disturbance of the whole system. Since the deficiency of poor ability of self-learning of fuzzy controller, fuzzy neural net(FNN) controllers for multi-input multi-output(MIMO) system were induced to the above two fuzzy controllers to resolve these problems. Simulation results of FNN controllers show that the proposed approach can achieve high displacement tracking accuracy and dynamic performance when the loads of the simulator are changeable or two hydraulic motors’ rotate speeds are different greatly.