A stage-cost reformulation of MPC lets users specify a desired time constant per task error, making tuning more intuitive while preserving the benefits of a prediction horizon.
Auto- mated tuning of nonlinear model predictive controller by reinforcement learning,
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From Instantaneous to Predictive Control: A More Intuitive and Tunable MPC Formulation for Robot Manipulators
A stage-cost reformulation of MPC lets users specify a desired time constant per task error, making tuning more intuitive while preserving the benefits of a prediction horizon.