An adaptive neural fuzzy sliding mode control scheme for rotational maneuvering and vibration suppression of a flexible spacecraft

This paper presents a simple and effective control technique for flexible nonlinear systems. The proposed control scheme is a combination of adaptive neural fuzzy control (ANFC) and sliding mode control (SMC). ANFC has a self-tuning mechanism based on gradient descent (GD) to find estimates of uncertain plant parameters, which are then provided to the SMC control law. The proposed control scheme is integrated with a rotating spacecraft system that has four flexible appendages. The system belongs to a class of flexible nonlinear discrete systems with infinite dimensions and highly coupled dynamics. The assumed mode method (AMM) is used to find the finite dimension model. The truncated model has uncertainties that make the system a challenging control problem. The purpose of the control scheme is to track the rotation angle of the spacecraft’s rigid hub while maintaining the deflections of the appendages. Adaptive proportional integral derivative (APID), direct ANFC and conventional SMC have also been implemented to provide a comparison with the proposed control scheme. The results show that the proposed control scheme has faster tracking performance and that appendage deflections also dissipate rapidly with the proposed control scheme.