Iterative feedback tuning (IFT) is a direct tuning method using closed loop experimental data. The method is based on numerical optimization. In each iteration of the optimisation an unbiased gradient estimate is used. In this contribution the results of are refined and developed further. Improvements are introduced on the optimization procedures of the IFT scheme to allow for joint optimization of non-conflicting criteria of stability robustness and performance. Also the case of weighted additive uncertainty is considered as an alternative to the co-prime factor perturbations as used by Glover and McFarlane (1989). Optimization of the estimate of the H/sub /spl infin// robustness criterion is now based on global optimization to increase re...
The aim of this paper is to extend iterative feedback tuning (IFT), which is a databased approach fo...
The Iterative Feedback Tuning (IFT) is a data-based method for the tuning of restricted-complexity c...
Iterative feedback tuning (IFT) is a data-based tuning approach that minimizes a quadratic performan...
Optimal performance of process control requires a controller synthesis based on a perfor-mance crite...
Iterative Feedback Tuning (IFT) is a data-based method for the iterative tuning of restricted comple...
The aim of this paper is to extend iterative feedback tuning (IFT), which is a data- based approach ...
Iterative feedback tuning (IFT) is a data-based method for the optimal tuning of a low order control...
Iterative feedback tuning (IFT) enables the data-driven tuning of controller parameters without the ...
International audienceIterative feedback tuning (IFT) is a data-based method for the tuning of restr...
Despite the vast amount of delivered theoretical results, regarding the topic of controller design, ...
Iterative feedback tuning (IFT) is a data-based method for the iterative tuning of restricted comple...
Iterative feedback tuning (IFT) is a widely used procedure for controller tuning. It is a sequence o...
Abstract: Iterative Feedback Tuning (IFT) is used for tuning PID controllers for the case when it is...
Abstract- Iterative Feedback Tuning is a purely data driven tuning algorithm for optimizing control ...
The aim of this paper is to extend iterative feedback tuning (IFT), which is a databased approach fo...
The Iterative Feedback Tuning (IFT) is a data-based method for the tuning of restricted-complexity c...
Iterative feedback tuning (IFT) is a data-based tuning approach that minimizes a quadratic performan...
Optimal performance of process control requires a controller synthesis based on a perfor-mance crite...
Iterative Feedback Tuning (IFT) is a data-based method for the iterative tuning of restricted comple...
The aim of this paper is to extend iterative feedback tuning (IFT), which is a data- based approach ...
Iterative feedback tuning (IFT) is a data-based method for the optimal tuning of a low order control...
Iterative feedback tuning (IFT) enables the data-driven tuning of controller parameters without the ...
International audienceIterative feedback tuning (IFT) is a data-based method for the tuning of restr...
Despite the vast amount of delivered theoretical results, regarding the topic of controller design, ...
Iterative feedback tuning (IFT) is a data-based method for the iterative tuning of restricted comple...
Iterative feedback tuning (IFT) is a widely used procedure for controller tuning. It is a sequence o...
Abstract: Iterative Feedback Tuning (IFT) is used for tuning PID controllers for the case when it is...
Abstract- Iterative Feedback Tuning is a purely data driven tuning algorithm for optimizing control ...
The aim of this paper is to extend iterative feedback tuning (IFT), which is a databased approach fo...
The Iterative Feedback Tuning (IFT) is a data-based method for the tuning of restricted-complexity c...
Iterative feedback tuning (IFT) is a data-based tuning approach that minimizes a quadratic performan...