Abstract: Iterative Feedback Tuning (IFT) is a data-based method for the tuning of restricted-complexity controllers with a standard H2 criterion which in general gives no a priori robustness guarantees. In this paper we elaborate on Loop Transfer Recovery (LTR) LQG synthesis techniques designed to achieve robustness of the feedback loop. We propose an IFT procedure that achieves approximate LTR and its associated robustness. The proposed procedure is illustrated with a numerical simulation example
Abstract: The objective of this contribution is to discuss three basic control design methods for di...
In this thesis the usage of the LPV-ARX representation of a LPV system for extending the applicabili...
A novel algorithm for tuning controllers for nonlinear plants is presented. The algorithm iterativel...
The approach of [5] for the solution of LQG/LTR by H∞, minimization of the recovery error is extende...
Optimal performance of process control requires a controller synthesis based on a perfor-mance crite...
computations associated with the LQG/LTR method in both the time-domain and the frequency-domain. On...
The difficult problem of robust stabilization and performance of dynamic systems under structured un...
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 method for the iterative tuning of restricted comple...
Abstract- Iterative Feedback Tuning is a purely data driven tuning algorithm for optimizing control ...
Despite the vast amount of delivered theoretical results, regarding the topic of controller design, ...
A robust Iterative Learning Control (ILC) design that uses state feedback and output injection for l...
For discrete-time non-minimum phase plants with feedback delays, we discuss two Loop Transfer Recove...
This paper considers the design of loop transfer recovery (LTR) controller for sampled-data systems....
The authors consider the problem of loop-transfer recovery (LTR) using prediction estimators for squ...
Abstract: The objective of this contribution is to discuss three basic control design methods for di...
In this thesis the usage of the LPV-ARX representation of a LPV system for extending the applicabili...
A novel algorithm for tuning controllers for nonlinear plants is presented. The algorithm iterativel...
The approach of [5] for the solution of LQG/LTR by H∞, minimization of the recovery error is extende...
Optimal performance of process control requires a controller synthesis based on a perfor-mance crite...
computations associated with the LQG/LTR method in both the time-domain and the frequency-domain. On...
The difficult problem of robust stabilization and performance of dynamic systems under structured un...
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 method for the iterative tuning of restricted comple...
Abstract- Iterative Feedback Tuning is a purely data driven tuning algorithm for optimizing control ...
Despite the vast amount of delivered theoretical results, regarding the topic of controller design, ...
A robust Iterative Learning Control (ILC) design that uses state feedback and output injection for l...
For discrete-time non-minimum phase plants with feedback delays, we discuss two Loop Transfer Recove...
This paper considers the design of loop transfer recovery (LTR) controller for sampled-data systems....
The authors consider the problem of loop-transfer recovery (LTR) using prediction estimators for squ...
Abstract: The objective of this contribution is to discuss three basic control design methods for di...
In this thesis the usage of the LPV-ARX representation of a LPV system for extending the applicabili...
A novel algorithm for tuning controllers for nonlinear plants is presented. The algorithm iterativel...