Process Control with Reinforcement Learning Multiple-input, multiple-output (MIMO) processes are a feature of almost all chemical plants. The design of robust control strategies is critical for maintaining consistent product quality, ensuring safe operations, minimizing downtime, and generating profit. Th...
MATLAB里自带的这个例子，试图训练出一个智能体，来通过髋、膝、踝三个关节的控制，使得让这个由两条腿...
Get an overview of reinforcement learning from the perspective of an engineer. Reinforcement learning is a type of machine learning that has the potential to solve some really hard control problems.
and manually fixing the policy. It will show some workarounds that make the policy more robust and the overall system safer. Lastly, it will show how you can use reinforcement learning to learn the parameters in a traditional control system and why, at the moment, th...
* The paper explores RL for optimum control of non-linear systems * Platform: MATLAB's Reinforcement Learning ToolBox (release R2019a) and Simulink * Run `main.m` to perform a test-run to ensure code is working. It runs 4 code files sequentially. It will train an agent with just 1...
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Invalid JSONThis project uses DDPG for optimal control of non-linear valves. Uses MATLAB and Simulink
Watch this webinar by Professor Rifat Sipahi from Northeastern University to learn about the curriculum materials his team developed for teaching RL and DRL with MATLAB®. The RL modules let students implement various applications such as grid-world navigation, temperature control, walking robots, ...
Reinforcement Learning Toolbox Request Trial Get Pricing 7:01Video length is 7:01 Inverted Pendulum Control with SimMechanics and QUARC 16:47Video length is 16:47 Kohler Builds Reliability Test System Using Data... 2:22Video length is 2:22 ...
Rigorous stability of the system has been proven via Lyapunov's direct method. Through Matlab simulation and experiment on the Quanser flexible link platform, the superiority and feasibility of the reinforcement learning control are verified. 展开 ...