In this paper, a novel phase-error-based Q-learning algorithm is proposed to solve the optimal tracking control problems for unknown discrete-time nonlinear systems. For the first time, phase errors between the system state and the desired trajectory are incorporated into the performance index, which rigorously guarant...
Bo-Yu Wen, Xin Chen, Wojciech Paszke et al.· International Journal of Con...· 0 citations
Robotic systems frequently operate under parametric uncertainties and constrained communication bandwidths, motivating data-driven control architectures that ensure optimal performance without explicit model identification. Conventional adaptive dynamic programming (ADP) methods for output-feedback control typically re...
Sasa Prodanovic, Emanuel Bernardi, X. Luan et al.· Conference proceedings· 0 citations
This paper proposes a novel iterative learning control (ILC) scheme for unknown affine nonlinear systems by integrating model-free feedback linearization with two-dimensional (2D) structure of the controlled dynamics. The approach eliminates the requirement for prior model knowledge by employing model reference adaptiv...
Boyu Wen, Xin Chen, Wojciech Paszke· International Conference on...· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.