Intelligent Adaptive Control Using LADP and IADP Applied to F-16 Aircraft with Imperfect Measurements

Linear Approximate Dynamic Programming (LADP) and Incremental Approximate Dynamic Programming (IADP) are Reinforcement Learning methods that seek to contribute to the field of Adaptive Flight Control. This paper assesses their performance and convergence, as well as the impact of sensor noise on policy convergence, online system...

Incremental model-based heuristic dynamic programming with output feedback applied to aerospace system identification and control

Sufficient information about system dynamics and inner states is often unavailable to aerospace system controllers, which requires model-free and output feedback control techniques, respectively. This paper presents a novel self-learning control algorithm to deal with these two problems by combining the advantages of heuristic dynamic...

Launch vehicle discrete-time optimal tracking control using global dual heuristic programming

Optimal tracking is a widely researched control problem, but the unavailability of sufficient information referring to system dynamics brings challenges. In this paper, an optimal tracking control method is proposed for an unknown launch vehicle based on the global dual heuristic programming technique. The nonlinear system dynamics is...