A new generic optimal controller structure and regulator design method are introduced avoiding the solution of polynomial equations. The model sensitivity properties of some combined identification and control schemes are investigated. It is shown that a new structure is superior to the others. An applicable strategy for iterative control refinement based on the generic scheme is presented and illustrated by simulation examples. A worst-case optimal input design algorithm is also introduced to increase the robustness of the closed-loop control in the relevant medium frequency range by generating a 'maximum-variance' reference signal. The adaptive version of the control refinement strategy is also shown with a special 'triple-control' exte...
This thesis presents theoretical and practical issues of local optimal control, which is one of the ...
Modeling and control design are typically subsequent but independent activities. Optimal control is ...
Abstract: We will argue in this paper that the nature and magnitude of model uncertainty dictate the...
This paper presents a novel unified approach of controller design and identification for unknown inp...
There are many aspects to consider when designing system identification experiments in control appli...
The problem of designing identification experiments to make them maximally informative with respect ...
In this report we study some different aspects of schemes for iterative identification and control d...
We compare open loop versus closed loop identification when the identified model is used for control...
International audienceIt is well known that the quality of the parameters identified during an ident...
A new concept has been developed for designing optimal feedback controllers that will be insensitive...
It is well known that the quality of the parameters identified during an identification experiment d...
The optimal steady-state control, and suboptimal adaptive control, of disturbed single-input-output ...
The work uses the method of standard characteristic polynomials, based on the Lyapunov theorem on ad...
Includes bibliography.This dissertation presents a comprehensive investigation of an optimalising co...
Special Issue Dedicated to Brian Anderson on the Occasion of His 70th Birthday: Part IIInternational...
This thesis presents theoretical and practical issues of local optimal control, which is one of the ...
Modeling and control design are typically subsequent but independent activities. Optimal control is ...
Abstract: We will argue in this paper that the nature and magnitude of model uncertainty dictate the...
This paper presents a novel unified approach of controller design and identification for unknown inp...
There are many aspects to consider when designing system identification experiments in control appli...
The problem of designing identification experiments to make them maximally informative with respect ...
In this report we study some different aspects of schemes for iterative identification and control d...
We compare open loop versus closed loop identification when the identified model is used for control...
International audienceIt is well known that the quality of the parameters identified during an ident...
A new concept has been developed for designing optimal feedback controllers that will be insensitive...
It is well known that the quality of the parameters identified during an identification experiment d...
The optimal steady-state control, and suboptimal adaptive control, of disturbed single-input-output ...
The work uses the method of standard characteristic polynomials, based on the Lyapunov theorem on ad...
Includes bibliography.This dissertation presents a comprehensive investigation of an optimalising co...
Special Issue Dedicated to Brian Anderson on the Occasion of His 70th Birthday: Part IIInternational...
This thesis presents theoretical and practical issues of local optimal control, which is one of the ...
Modeling and control design are typically subsequent but independent activities. Optimal control is ...
Abstract: We will argue in this paper that the nature and magnitude of model uncertainty dictate the...