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About Data Driven Control of Interacting Two Tank Hybrid System Using Deep Reinforcement Learning
This document discusses using deep reinforcement learning to control an interacting two tank hybrid system. Specifically, it uses deep deterministic policy gradient (DDPG), an actor-critic reinforcement learning algorithm, to learn a controller for the nonlinear system. DDPG is able to learn effective control policies directly from raw sensor data without an engineering model of the system dynamics. The document reviews related work applying reinforcement learning methods like DDPG, TD3, and PPO to control problems. It is concluded that reinforcement learning is a promising approach for data-driven control of complex, nonlinear systems.
Detailed Information
| Author: | ['ayush sharma'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 7 |
| Language: | English |
| Format: | |
| Price: | FREE |
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