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The controller parameters analyzed were prediction and control horizons, suppression factor, reference trajectory and integral factor.
Furthermore, equivalent control concept allows a straightforward tuning of the controller parameters.
Controller parameters were set manually on the first day, and fine-tuned at the beginning of each session based on the behavior of each rat.
Controller parameters Kp and Ki were set manually on the first recording session, and fine-tuned for each animal at the beginning of each session.
By the rule, controller parameters can be self-regulated.
Design rules for the controller parameters are available.
BFOA is employed to search for optimal controller parameters.
This leads to constraints on the controller parameters.
In addition the controller parameters are optimized using PSO approach.
In Auto mode, the controller parameters are derived automatically.
This goal is achieved by properly defining the controller parameters.
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