A receding-horizon regulator for nonlinear systems and a neural approximation

  title={A receding-horizon regulator for nonlinear systems and a neural approximation},
  author={Thomas Parisini and Riccardo Zoppoli},
Abstiaet-A receding-horizon (RH) optimal control scheme for a discrete-time nonlinear dynamic system is presented. A nonquadratic cost function is considered, and constraints are imposed on both the state and control vectors. Two main contributions are reported. The first consists in deriving a stabilizing regulator by adding a proper terminal penalty function to the process cost. The control vector is generated by means of a feedback control law computed off line instead of computing it on… CONTINUE READING
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