一种空间飞行器姿态控制非线性模型的预测控制新算法

空间飞行器的姿态控制受到诸如带时延的非线性动态特性、模型和参数的不确定性等因素的影响 ,其控制相当复杂。传统的控制技术 (如PID控制 )对控制对象的过程模型要求较高 ,且不能解决过程控制中非线性、时变、控制输入的约束性等因素的影响 ,其控制所能达到的性能和效率也远不够满足当前飞行器的控制要求。该文将介绍一种新型的基于控制输入的函数空间最优化的模型预测控制算法 ,称为函数空间模型预测控制 (F -MPC)。该法可用于线性和非线性系统 ,对过程模型要求不高 ,能在控制输入约束条件存在的情况下通过在线优化使系统很好地跟踪期望轨迹 ,并且解决了PID控制所遇到的问题。同时 ,将该算法用于空间飞行器的姿态控制仿真 ,仿真结果表明控制效果很好。

Attitude Control of Spacecraft using Nonlinear Model Predictive Control

Spacecraft attitude control during propulsive maneuvers is complicated due to several factors such as nonlinear dynamics with time delays, modeling and parameter uncertainties. Classical control techniques such as PID control need explicit modeling and failing to take into account process characteristics such as nonlinearities, time variations and constraints. Its control criteria doesn't meet the demands of modern control. A new methodology for Model Predictive Control based on a function-space optimization of control inputs is presented, which is termed Function-space Model Predictive Control. This methodology is an optimal control approach involving direct use of system models (linear and nonlinear) and on-line optimization to follow a desired trajectory subjected to the various constraints on the control inputs. It can solve the problems encountered by PID control. Furthermore, simulation of spacecraft attitude control is executed by this methodology, Simulation results are presented illustrating the application of this methodology to three-axis attitude control of fully-actuated and underacutuated spacecraft.