Input-output (I-O) feedback linearization suffers from a number of restrictions which have limited its use in model-based predictive control. Some of these restrictions do not apply to the case of bilinear systems, but problems with input constraints and unstable zero dynamics persist. The present note overcomes these difficulties by means of an interpolation strategy. Involved in this interpolation is a feasible and stabilizing trajectory, which is computed through the use of invariant feasible sets, and a more aggressive trajectory, which can be chosen to be either the unconstrained optimal trajectory or any alternative one
International audienceWe propose a new approach to controlling a discrete linear stationary system w...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
Abst ract: In this paper a new model predictive control (MPC) strategy, applicable to a set of nonl...
Feedback linearization suffers from a number of restrictions which have limited its use in Model-bas...
Relative degree and nonminimum phase difficulties limit the applicability of input-output feedback l...
Interpolation between unconstrained optimal input trajectories and feasible trajectories forms the b...
Earlier work used partial invariance to identify regions in state space where feedback linearization...
This paper describes a method for calculating invariant/feasible sets with respect to feedback linea...
Linear terminal control laws In model predictive control imply the need to compromise between perfor...
International audienceThe paper deals with the control of linear discrete-time systems in presence o...
Interpolation involving constrained optima offers distinctive advantages for linear and non-linear m...
MPC(Model Predictive Control) is representative of control methods which are able to handle physical...
matrix inequalities An efficient robust model predictive control (MPC) strategy using augmented elli...
This study proposes a linear Model Predictive Control (MPC) method that combines high prediction acc...
International audienceWe present some improvements on interpolation based control (IC) for linear di...
International audienceWe propose a new approach to controlling a discrete linear stationary system w...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
Abst ract: In this paper a new model predictive control (MPC) strategy, applicable to a set of nonl...
Feedback linearization suffers from a number of restrictions which have limited its use in Model-bas...
Relative degree and nonminimum phase difficulties limit the applicability of input-output feedback l...
Interpolation between unconstrained optimal input trajectories and feasible trajectories forms the b...
Earlier work used partial invariance to identify regions in state space where feedback linearization...
This paper describes a method for calculating invariant/feasible sets with respect to feedback linea...
Linear terminal control laws In model predictive control imply the need to compromise between perfor...
International audienceThe paper deals with the control of linear discrete-time systems in presence o...
Interpolation involving constrained optima offers distinctive advantages for linear and non-linear m...
MPC(Model Predictive Control) is representative of control methods which are able to handle physical...
matrix inequalities An efficient robust model predictive control (MPC) strategy using augmented elli...
This study proposes a linear Model Predictive Control (MPC) method that combines high prediction acc...
International audienceWe present some improvements on interpolation based control (IC) for linear di...
International audienceWe propose a new approach to controlling a discrete linear stationary system w...
The control based on online optimization, popularly known as model predictive control (MPC), has lon...
Abst ract: In this paper a new model predictive control (MPC) strategy, applicable to a set of nonl...