Reinforcement learning-based optimal control of uncertain nonlinear systems
Miguel García, Wenjie Dong
Abstract
This paper considers the optimal control of a second-order nonlinear system with unknown dynamics. A new reinforcement learning based approach is proposed with the aid of direct adaptive control. By the new approach, actor-critic reinforcement learning algorithms are proposed with neural network approximation. Simulation results are presented to show the effectiveness of the proposed algorithms.
Topics & Concepts
Reinforcement learningArtificial neural networkNonlinear systemComputer scienceControl (management)Optimal controlControl theory (sociology)Artificial intelligenceMathematical optimizationMathematicsQuantum mechanicsPhysicsAdaptive Dynamic Programming ControlAdaptive Control of Nonlinear SystemsReinforcement Learning in Robotics