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## Ansys Sweep Model, Pybullet Simulation Environment, and Reinforcement Learning Controller for HEMS Magnetic Levitation
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This repository contains files with Ansys Parametric Sweep data, polynomial interpolation of this data, PyBullet simulation
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interfacing with this data and drawing from physical constraints on the actual chassis, and trial reinforcement learning models
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that learn from the environment based on a defined cost function.
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#### Upcoming objectives
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1. Verify again that sweep interpolation data provides reasonable estimates of real-world forces and torques using load cell
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2. Implement PID controller that interfaces with the simulation environment present in ```lev_env.py```
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3. Implement other forms of reinforcement learning control, look into designing a reward structure that is conducive to learning, and
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overall dive into more research on reinforcement learning algorithms for very sensitive tasks that are intrinsically highly unstable.
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