Spacecraft Attitude Control Using Approximate Receding-Horizon Model-Error Control Synthesis

Model-error control synthesis is a nonlinear robust control approach that mitigates the effects of modeling errors and disturbances on a system by providing corrections to the nominal control input directly. In this paper model-error control synthesis is applied to the spacecraft attitude control problem, where the model-error vector is computed using a receding-horizon approximation. The main advantage of this approach over other adaptive approaches for spacecraft attitude control is that it can simultaneously handle both inertia modeling errors and time varying disturbances. A design scheme is presented to determine the weighting factor and the length of the associated receding-horizon interval of the model-error solution by minimizing the closed-loop sensitivity norm. Simulation results are provided to show the performance of the new control approach.

[1]  John L. Crassidis,et al.  LINEAR STABILITY ANALYSIS OF MODEL ERROR CONTROL SYNTHESIS , 2000 .

[2]  John L. Crassidis,et al.  Fundamental relation of approximate receding-horizon optimization to the simple mass-spring-damper system , 2003 .

[3]  J. Junkins,et al.  Stereographic Orientation Parameters for Attitude Dynamics: A Generalization of the Rodrigues Parameters , 1996 .

[4]  Dennis S. Bernstein,et al.  Adaptive Asymptotic Tracking of Spacecraft Attitude Motion with Inertia Matrix Identification , 1998 .

[5]  Giuseppe Carlo Calafiore,et al.  Randomized algorithms for probabilistic robustness with real and complex structured uncertainty , 2000, IEEE Trans. Autom. Control..

[6]  J. Junkins,et al.  Optimal Estimation of Dynamic Systems , 2004 .

[7]  M. Akella,et al.  Globally stabilizing saturated attitude control in the presence of bounded unknown disturbances , 2005 .

[8]  John L. Crassidis,et al.  Robust Control of Nonlinear Systems Using Model-Error Control Synthesis , 1999 .

[9]  John L. Junkins,et al.  Adaptive control of nonlinear attitude motions realizing linear closed-loop dynamics , 1999, Proceedings of the 1999 American Control Conference (Cat. No. 99CH36251).

[10]  John L. Crassidis,et al.  Predictive filtering for attitude estimation without rate sensors , 1997 .

[11]  John L. Crassidis,et al.  NONLINEAR PREDICTIVE CONTROL OF SPACECRAFT , 1997 .

[12]  H. Chernoff.  A Measure of Asymptotic Efficiency for Tests of a Hypothesis Based on the sum of Observations , 1952 .

[13]  John L. Crassidis,et al.  Predictive Filtering for Nonlinear Systems , 1996 .

[14]  Rajesh Rajamani,et al.  Vehicle dynamics and control , 2005 .

[15]  Haiyan Hu,et al.  Robust Stability Test for Dynamic Systems with Short Delays by Using Padé Approximation , 1999 .

[16]  John L. Crassidis,et al.  ROBUST SPACECRAFT ATTITUDE CONTROL USING MODEL-ERROR CONTROL SYNTHESIS , 2002 .

[17]  P. Lu.  Approximate nonlinear receding-horizon control laws in closed form , 1998 .

[18]  Bong Wie,et al.  Space Vehicle Dynamics and Control , 1998 .

[19]  John L. Crassidis,et al.  MODEL-ERROR CONTROL SYNTHESIS USING APPROXIMATE RECEDING-HORIZON CONTROL LAWS , 2001 .

[20]  Anke Xue,et al.  Quadratic guaranteed cost analysis for a class of nonlinear uncertain systems , 2001, Proceedings of the 2001 IEEE International Conference on Control Applications (CCA'01) (Cat. No.01CH37204).