Learning from adaptive control of a class of space manipulator systems

Stability issues for mode-based control of space manipulator systems are studied in this paper. The technique used is to employ a newly developed deterministic learning (DL) theory, by defining a tracking control task as a reference mode, identification of which is achieved in a local region via DL. Likewise, identification of the local controlled manipulator system dynamics corresponding to each reference mode is also realized. Then a set of mode-based constant NN controllers are constructed accordingly by using the obtained manipulator system dynamics. When tracking control task begins to change, rapid recognition of reference mode is naturally implemented due to the internal matching for reference system dynamics, then the corresponding NN controller with learned experience is selected and activated. Research results show that the mode-based NN controllers can guarantee the stability of the mode-based space manipulator systems and improve the control performance. Finally, numerical simulations of space manipulator systems have demonstrated the effectiveness of the proposed approach. © 2015, Editorial Dept. of JA. All right reserved.