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The onboard subsystem controller based on PID control will achieve the motion control under the optimal command.
This control method adjusts a controller based on past system and environmental data.
A nonlinear controller based on sliding mode control theory is designed.
The fuzzy system is designed to mimic an ideal controller, based on sliding-mode control.
We present a novel adaptive explicit dual controller based on model predictive control (MPC).
Then, one can design a controller based on Eq. (9).
Real-time control is also achievable with model predictive controller based on convex formulation.
The controller based on a difference equation uses short control horizon.
An optimal excitation controller based on the theory of linear optimal control is designed.
Our goal was to reduce the duration of poorly controlled haemodynamic status by using a closed-loop controller based on fuzzy logic in septic patients.
Controller based on those solutions was verified successfully by simulation.
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