控制受限的卫星轨道转移过程中的姿态控制

Attitude control of satellite in process of orbit transfer with constraint input

摘要:

针对刚体卫星在轨道转移过程中存在由质心漂移和推力偏心产生干扰力矩的控制问题,考虑存在参数不确定性、外部干扰以及控制输入受限,提出了一种智能自适应滑模控制方法,这种方法继承了传统自适应滑模控制的优点的同时,利用神经网络的逼近能力来补偿执行机构的饱和非线性,进而满足执行机构的幅值受限的要求．最后将该方法应用于卫星的轨道转移过程中,结果表明了方法的有效性与可行性．

Abstract:

In this paper, a neural network based on adaptive sliding mode controller for rigid spacecraft is proposed, in which the external disturbance that is caused by drift of mass’s center and thruster misalignment, uncertain parameters and actuator saturation are explicitly taken into account. More specifically, this input saturation nonlinearity is assumed to be unknown in advance and as disturbance. By using the characteristics of neural network (NN), the NN-based compensator is developed to compensate the effect of this saturation nonlinearity. Under this, a novel adaptive sliding mode controller is designed to reject the disturbance and deal with uncertainty due to the thruster misalignment and the center drift, in which the requirement of knowing the system parameters in advance is eliminated by using an adaptive updating technique. Systematic design procedure is also developed for synthesis of the NN adaptive sliding mode attitude control strategy. Simulation results show the theoretical and practical merit of the designed approach.