Output feedback control of anti‐linear systems using adaptive dynamic programming

This paper introduces an adaptive optimal feedback control approach for discrete‐time anti‐linear systems (ALSs). The method utilizes sampling and measurable input–output data. By employing the Adaptive Dynamic Programming (ADP) technique, this study iteratively solves the discrete‐time algebraic Anti‐Riccati equation (AARE). Initially, an output feedback model is established for ALSs, and a model‐based algorithm is developed based on this model. The feasibility of this algorithm is based on the premise that the system dynamic information is completely known. Subsequently, for the scenario where the model is unknown, we further developed a model‐free ADP algorithm specifically designed to address optimal control problems in the presence of model uncertainty. With this algorithm, we achieve effective control optimization even in cases where detailed system dynamics information is lacking. Finally, through simulation experiments, we validated the feasibility and effectiveness of this algorithm.