Abstract This paper proposes a data-driven control allocation scheme for input redundant linear time-invariant systems. Contrary to the existing literature, the present work is built on a static state feedback controller with row-sparse structure that generates a virtual stabilizing input for control allocation problem. It is emphasized that a stabilizing row-sparse static state feedback controller always exists if the system is controllable and has input redundancy. With a set of available input-state data, a stabilizing controller is designed in linear matrix inequality framework. The system matrix A and the input matrix B are assumed to be unknown. For control allocation, however, we have assumed that the linear dependence information of actuators is available. Both the continuous-time and the discrete-time systems have been considered. The pole placement technique has also been included in data-driven design framework to ensure certain closed-loop performances. To demonstrate the effectiveness of the methodology, the proposed allocation approach is applied to two systems: a satellite launch vehicle model and an innovative control effector aircraft model.
Building similarity graph...
Analyzing shared references across papers
Loading...
Aritra Sinha
S Patra
Journal of Dynamic Systems Measurement and Control
Indian Institute of Technology Kharagpur
Building similarity graph...
Analyzing shared references across papers
Loading...
Sinha et al. (Sat,) studied this question.
www.synapsesocial.com/papers/69a52dbff1e85e5c73bf0e53 — DOI: https://doi.org/10.1115/1.4071258