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文章给出了存在不确定质量参数和扰动时航天器进行姿态机动的控制系统。控制法则由神经网络和线性控制逻辑组成,这是为预定参数轨道飞行的航天器设计的。为得到闭环稳定条件使用了李雅普诺夫稳定性理论。这些稳定性条件施加到神经网络上起网络可调权重主控调整的约束作用。模拟结果证明当航天器惯量发生变化和出现干扰时,所提出的控制法则具有良好的跟踪特性。除了良好的鲁棒特性,模拟结果还证明由于所提出的神经网络控制器显示出网络权重迅速收敛,说明控制器具有学习能力。
In this paper, a control system of attitude maneuver of spacecraft with uncertain quality parameters and disturbances is given. The law of control consists of a neural network and linear control logic, which is designed for orbiting spacecraft with predetermined orbital parameters. In order to obtain closed-loop stability conditions, Lyapunov stability theory is used. These stability conditions are imposed on the neural network as a constraint of the network tunable weight master control. Simulation results show that the proposed control law has good tracking characteristics when spacecraft inertia changes and disturbance occurs. In addition to good robustness, the simulation results also show that the controller has the learning ability because the proposed neural network controller shows that the network weights converge rapidly.