Attitude Control of Planar Space Robot based on Self-Organizing Polynomial Data Mining Algorithm

Y.W. Kim, T. Narikiyo, and J.-H. Kim (Japan)


Planar Space Robot, Data Mining Algorithm, Model Predictive Control, Caplygin System


This paper presents a new method for the attitude control of planar space robots. In order to control highly constrained non-linear system such as a 3D space robot, the analyti cal formulation for the system with complex dynamics and effective control methodology based on the formulation, are not always obtainable. In the proposed method, cor respondingly, a non-analytical but effective self-organizing modeling method for controlling a highly constrained sys tem is proposed based on a polynomial data mining algo rithm. In order to control the attitude of a planar space robot, it is well known to require inputs characterized by a special pattern in time series with a non-deterministic length. In order to correspond to this type of control paradigm, we adopt the Model Predictive Control (MPC) scheme where the length of the non-deterministic horizon is determined based on implementation cost and control performance. The optimal solution to ļ¬nding the size of the input pattern is found by a solving two-stage program ming problem.

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