Control

Reinforcement Learning is Direct Adaptive Optimal Control

Reinforcement Learning is Direct Adaptive Optimal Control How should Reinforcement learning be viewed from a control systems perspective? Control problems can be divided into two classes: regulation and tracking problems, in which the objective is to follow a reference trajectory. optimal control problems, which the objective is to extremize a functional of the controlled system’s… read more »

Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach

Decentralized Stabilization for a Class of Continuous-Time Nonlinear Interconnected Systems Using Online Learning Optimal Control Approach Neural-network-based Online Learning Optimal Control Decentralized Control Strategy Cost functions (critic neural networks) – local optimal controllers Feedback gains to the optimal control policies – decentralized control strategy Optimal Control Problem (Stabilization) Hamilton-Jacobi-Bellman (HJB) Equations Apply Online Policy Iteration… read more »

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