Suboptimal Performance of Receding Horizon Control with Unknown Linear Systems and Its Applications in Learning-Based Control
The core message of this article is to provide a novel suboptimality analysis of a nominal receding-horizon linear quadratic (LQ) controller under the joint effect of modeling error, terminal value function error, and prediction horizon. The analysis reveals that for many cases, the prediction horizon can be either 1 or infinity to improve the control performance, depending on the relative difference between the modeling error and the terminal value function error.
Robust Feedback Stability Analysis for Systems with Simultaneous Gain and Phase Uncertainty
The core message of this article is to derive less conservative sufficient conditions for the robust feedback stability of linear time-invariant systems involving sectored-disk uncertainty, which encompasses simultaneous gain and phase constraints on the uncertain dynamics.
Efficient Computation of Minimal and Maximal Backward Reachable Sets for Perturbed Continuous-Time Linear Systems
The core message of this article is to present efficient algorithms for computing inner and outer approximations of the minimal and maximal backward reachable sets for perturbed continuous-time linear systems. The proposed approaches scale polynomially with the state dimension, enabling the analysis of high-dimensional systems.