Specifically, these properties are continuity, differentiability and monotonicity. This paper presents both numerical and analytical results to reveal the ...
Specifically, these properties are continuity, differentiability and monotonicity. This paper presents both numerical and analytical results to reveal the ...
This paper presents both numerical and analytical results to reveal the smoothness properties of the value function, which may contradict the traditional ...
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What is the prediction horizon in MPC?
This paper presents both numerical and analytical results to reveal the smoothness properties of the value function. Increasing sampling rate and/or prediction ...
This paper presents analytical results to reveal the smoothness properties of the MPC value function in open- and closed-loop for constrained linear systems.
Model predictive control (MPC) is an optimal control technique in which the calculated control actions minimize a cost function for a constrained dynamical ...
Sep 21, 2015 · Smoothness properties of the MPC value function in open and closed-loop with respect to sampling time and prediction horizon. In IEEE Asian ...
This paper presents analytical results to reveal the smoothness properties of the MPC value function in open- and closed-loop for constrained linear systems.
The proposed approach focuses on the tuning of structural MPC parameters, namely sampling time and prediction horizon length, to produce a set of optimal ...
Between sampling times the curves were computed by integrating the nominal model. Both states and the control converge quickly to the desired target values.
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