IBUKI TATSUYA    Department   Undergraduate School  , School of Science and Technology    Position   Associate Professor
Language	English
Publication Date	2020/01
Type	Academic Journal
Peer Review	Peer reviewed
Title	Real-Time Model Predictive Control of Rigid Body Motion via Discretization Using the Cayley Map
Contribution Type	Co-authored (other than first author)
Journal	IEEE Access
Journal Type	Another Country
Publisher	The Institute of Electrical and Electronics Engineers (IEEE)
Volume, Issue, Page	8,pp.17149-17159
Total page number	11
Author and coauthor	Yuichi Tadokoro, Yuki Taya, Tatsuya Ibuki, Mitsuji Sampei
Details	This paper presents a fast nonlinear model predictive control method for rigid body dynamical systems such as spacecraft or aerial vehicles on the special Euclidean group SE(3). The focus of this research is on the real-time execution of the optimal control on a low-cost embedded computer. The position and orientation of a rigid body are expressed as a 6-dimensional vector via the Cayley map for SE(3). Based on the representation, the motion can be exactly discretized on the algebra se(3). As a result, coarse sampling intervals can be selected to reduce the number of prediction steps. Furthermore, the recursive discretization technique is applied to effectively reduce the decision variables of the nonlinear optimization problem by eliminating states from them. Simulation results on a Raspberry Pi single-board computer are given to prove that the present model predictive control method is feasible in real time.