We provide a new sequential predictors approach for the exponential stabilization of linear time-varying systems. Our method circumvents the problem of constructing and estimating distributed terms in the control laws, and allows arbitrarily large input delay bounds, pointwise time-varying input delays, and uncertainties. Instead of using distributed terms, our approach to handling longer delays is to increase the number of predictors. We obtain explicit formulas to find lower bounds for the number of required predictors. The formulas involve bounds on the delays and on the derivatives of the delays. We illustrate our method in three examples
We provide a reduction model approach for achieving global exponential stabilization of linear syste...
International audienceWe provide a reduction model approach for achieving global exponential stabili...
A recent work by Mazenc and Malisoff provides a trajectory-based approach for proving stability of t...
International audienceWe provide a new sequential predictors approach for the exponential stabilizat...
International audienceWe provide a new sequential predictors approach for the exponential stabilizat...
In a 2016 IEEE Conference on Decision and Control paper, our team designed sequential predictors for...
We provide new sequential predictors for a large class of linear time-varying systems that contain c...
We study time-varying linear discrete time systems with uncertainties and time-varying measurement d...
International audienceWe study time-varying linear discrete time systems with uncertainties and time...
We provide sequential predictors for delayed time-varying discrete time linear systems with outputs,...
We build sequential predictors for time-varying linear systems with time-varying input delays, outpu...
International audience—We propose a prediction based stabilization approach for a general class of n...
International audienceIn a 2016 IEEE Conference on Decision and Control paper, our team designed seq...
We propose a prediction based stabilization approach for a general class of nonlinear time-varying s...
[EN] For input delayed systems, the sequential subpredictor (SSP) control scheme has the advantage t...
We provide a reduction model approach for achieving global exponential stabilization of linear syste...
International audienceWe provide a reduction model approach for achieving global exponential stabili...
A recent work by Mazenc and Malisoff provides a trajectory-based approach for proving stability of t...
International audienceWe provide a new sequential predictors approach for the exponential stabilizat...
International audienceWe provide a new sequential predictors approach for the exponential stabilizat...
In a 2016 IEEE Conference on Decision and Control paper, our team designed sequential predictors for...
We provide new sequential predictors for a large class of linear time-varying systems that contain c...
We study time-varying linear discrete time systems with uncertainties and time-varying measurement d...
International audienceWe study time-varying linear discrete time systems with uncertainties and time...
We provide sequential predictors for delayed time-varying discrete time linear systems with outputs,...
We build sequential predictors for time-varying linear systems with time-varying input delays, outpu...
International audience—We propose a prediction based stabilization approach for a general class of n...
International audienceIn a 2016 IEEE Conference on Decision and Control paper, our team designed seq...
We propose a prediction based stabilization approach for a general class of nonlinear time-varying s...
[EN] For input delayed systems, the sequential subpredictor (SSP) control scheme has the advantage t...
We provide a reduction model approach for achieving global exponential stabilization of linear syste...
International audienceWe provide a reduction model approach for achieving global exponential stabili...
A recent work by Mazenc and Malisoff provides a trajectory-based approach for proving stability of t...