In this paper, an offline model predictive control (OMPC) based on the linear parameter varying (LPV) model is developed for free-floating space robots. Parameter set mapping (PSM) is employed to obtain an LPV model with fewer scheduling parameters, which can enable easier control design and achieve more objectives by using linear control methods. In terms of the LPV system with external disturbance, a model predictive control (MPC) method is proposed. Since large disturbance to the base attitude is not admissible in certain missions such as communication with the earth, a term related to the base angular velocity is considered as a part of the cost function of MPC. To deal with actuator saturation, input limitations are included in the constraints of MPC. Moreover, an offline algorithm is introduced to reduce the online computation. Numerical simulations are presented to demonstrate the effectiveness of the proposed method.
LPV-Based Offline Model Predictive Control for Free-Floating Space Robots
Rocco P.;
2021-01-01
Abstract
In this paper, an offline model predictive control (OMPC) based on the linear parameter varying (LPV) model is developed for free-floating space robots. Parameter set mapping (PSM) is employed to obtain an LPV model with fewer scheduling parameters, which can enable easier control design and achieve more objectives by using linear control methods. In terms of the LPV system with external disturbance, a model predictive control (MPC) method is proposed. Since large disturbance to the base attitude is not admissible in certain missions such as communication with the earth, a term related to the base angular velocity is considered as a part of the cost function of MPC. To deal with actuator saturation, input limitations are included in the constraints of MPC. Moreover, an offline algorithm is introduced to reduce the online computation. Numerical simulations are presented to demonstrate the effectiveness of the proposed method.File | Dimensione | Formato | |
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