In this paper, SLEWING maneuver of a flexible spacecraft with a large angle of rotation is considered and, assuming structural frequency uncertainties, a robust minimum-time optimal CONTROL law is developed. Considering typical bang-bang CONTROL commands with multiple symmetrical switches, a parameter optimization procedure is introduced to find the CONTROL forces/torques. The constrained minimization problem is augmented with the robustness constraints, which in turn increases the number of switches in the bang-bang CONTROL input to match the total number of the constraint equations. The steps of the solution algorithm to obtain the time optimal CONTROL input are discussed next. The developed CONTROL law is applied to a given satellite during a SLEWING maneuver. The simulation results show that the robust CONTROL input with just few switching times can significantly lessen the vibrating motion of the flexible appendage in the presence of structural frequency uncertainties, which reveals the merits of the developed CONTROL law      

In this paper, minimum and near-minimum time optimal CONTROL laws are developed and compared for a rigid space platform with flexible links during an orientating maneuver with a large angle of rotation. The CONTROL commands are considered as typical bang-bang with multiple symmetrical switches, the time optimal CONTROL solution for the rigid-body mode is obtained as a bang bang function and applied to the flexible system after smoothening the CONTROL inputs to avoid stimulation of the flexible modes. This will also reflect practical limitations in exerting bang-bang actuator forces/torques due to delays and non-zero time constants of existing actuation elements. The smoothness of the input command is obtained by reshaping its profile based on consideration of additional derivative constraints. the optimal CONTROL problem is converted into parameter optimization problem. The steps of the solution procedure and numerical algorithm to obtain the time optimal CONTROL input are discussed next. The developed CONTROL law is applied to a given satellite during a SLEWING maneuver. The simulation results show that the CONTROL input with just a few switching times can significantly lessen the vibrating motion of the flexible appendage, which reveals the merits of the developed CONTROL law. The modified realistic optimal input compared to the bang-bang solution goes well with the practical limitations and alleviates the vibrating motion of the flexible appendage, which reveals the merits of the new developed CONTROL law.

SLEWING bearing, which is widely applied in tank, excavator and wind turbine, is a critical component of rotational machines. Standard procedure for bearing life calculation and condition assessment has been established for general rolling bearings. Nevertheless, relatively less literatures in regard to the health condition assessment of SLEWING bearing has been published in past. Real time health condition assessment for SLEWING bearing is used for avoiding catastrophic failures by detectable and preventative measurement. In this paper, a new strategy is presented for health evaluation of SLEWING bearing based on multiple characteristic parameters, and ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System) models are demonstrated to predict the health condition of SLEWING bearings. The prediction capabilities offered by ANN and ANFIS are shown by data obtained from full life test of SLEWING bearings in NJUT test System. Various statistical performance indexes have been utilized to compare the performance of two predicted models. The results suggest that ANFIS-based prediction model outperforms ANN models.