TY  - JOUR
TI  - Constrained discrete-time optimal control of uncertain systems with adaptive
Lyapunov redesign
AB  - In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using
functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization
theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the
redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online
approximation of uncertainties acting on both physical system and state estimator can be obtained. Moreover, the
convergence criteria for online parameter adaptation with fully matched and partially matched cases are presented and
shown. In addition, it is shown that the uniform boundedness of tracking and adaptation errors can be maintained by
projection-based parameter update laws in discrete-time with adequate sampling times. Finally, the proposed method
is implemented to quadrotor case study and the gradual recovery of feasible sub-optimal solutions are presented despite
actuation, modeling and measurement errors. By using the proposed method, the uncertainty estimates are successfully
converged to their prescribed values and both state prediction and command tracking of model predictive controller are
corrected within the convergence bounds.
AU  - Turgut, Ali Emre
AU  - Altintas, Oguz Han
DO  - 10.3906/elk-2011-8
PY  - 2021
JO  - Turkish Journal of Electrical Engineering and Computer Sciences
VL  - 29
IS  - 3
SN  - 1300-0632
SP  - 1836
EP  - 1851
DB  - TRDizin
UR  - http://search/yayin/detay/523597
ER  -