Automated tuning of nonlinear model predictive controller by reinforcement learning
One of the major challenges of model predictive control (MPC) for robotic applications is the non-trivial weight tuning process while crafting the objective function. This process is often executed using the trial-and-error method by the user. Consequently, the optimality of the weights and the time...
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Main Authors: | , , |
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Format: | Conference or Workshop Item |
Language: | English |
Published: |
2020
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Online Access: | https://hdl.handle.net/10356/143042 |
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Institution: | Nanyang Technological University |
Language: | English |