Continuous-time reinforcement learning (CT-RL) algorithms hold great promise in real-world control applications. Adaptive dynamic programming (ADP)-based CT-RL algorithms, especially their theoretical developments, have achieved great successes. However, these methods have not been demonstrated for solving realistic or meaningful learning control problems....

This algorithm is developed in the field of control systems for control of affine nonlinear continuous time (CT) systems, which include important application areas such as robotics and autonomous systems, aerospace, manufacturing, and process control. This invention falls under the class of continuous-time reinforcement learning (CT-RL) control algorithms....