A Simplified Multi-Input Multi-Output Formulation for the Quantitative Feedback Theory

1992 ◽  
Vol 114 (2) ◽  
pp. 179-185 ◽  
Author(s):  
O. Yaniv ◽  
Y. Chait
Keyword(s):  
Linear Functions ◽  
Model Matching ◽  
Quantitative Feedback Theory ◽  
Matching Problem ◽  
Performance Constraints ◽  
Robust Model ◽  
Traditional Procedure ◽  
Step Procedure ◽  
Loop Transfer Function ◽  
And Control

A simplified multi input/output formulation is developed for the quantitative feedback theory (QFT) for the 2 × 2 (n = 2) case. This formulation is consistent with traditional QFT philosophy where performance is specified for each individual closed-loop transfer function and control bandwidths are minimized. The simplified formulation turns the solution of a simultaneous robust stability and robust model matching problem into a two (n in general) step procedure of solving quadratic inequalities (whose coefficients are linear functions of the plants and the performance constraints); the traditional procedure requires six (n + n2 in general) steps for a similar problem. A numerical example illustrates the simplified formulation and demonstrates its ability to offer useful insight in a control design.

scholarly journals A Robust Controller for Multivariable Model Matching System Utilizing a Quantitative Feedback Theory: Application to Magnetic Levitation

2019 ◽  
Vol 9 (9) ◽  
pp. 1753 ◽  
Author(s):  
Ramamurthy Jeyasenthil ◽  
Seung-Bok Choi
Keyword(s):  
Controller Design ◽  
Magnetic Levitation ◽  
Design Method ◽  
External Disturbance ◽  
Uncertain System ◽  
Disturbance Attenuation ◽  
Model Matching ◽  
Quantitative Feedback Theory ◽  
Matching Problem ◽  
And Control

This paper proposes a systematic feedback controller design methodology for multi-input multi-output (MIMO) uncertain systems using the quantitative feedback theory (QFT). To achieve this goal, the model matching problem was considered and the inversion feedforward controller was designed to improve control performance while reducing the demand on feedback control alone. The proposed method is formulated based on the concept of equivalent disturbance attenuation (EDA) approach in which the uncertain system problem is converted into an external disturbance rejection problem based on a nominal system. This proposed approach exhibiting non-sequential design method result in the suboptimal solution showing design simplicity and computational efficiency compared to the existing method. In order to validate the effectiveness of the proposed control methodology, the MIMO magnetic levitation system as adopted and control performances such as time response were presented in both time and frequency domains.

scholarly journals The discrete-time tracking problem with H∞ model matching approach plus integral control

2019 ◽  
Vol 292 ◽  
pp. 01018
Author(s):  
Murat Akın ◽  
Tankut Acarman
Keyword(s):  
Discrete Time ◽  
Closed Loop ◽  
Controller Design ◽  
Model Matching ◽  
Matching Problem ◽  
Design Algorithm ◽  
Integral Control ◽  
Loop Transfer Function ◽  
Model Transfer ◽  
Static Output

In this study, the discrete-time H∞ model matching problem with integral control by using 2 DOF static output feedback is presented. First, the motivation and the problem is stated. After presenting the notation, the two lemmas toward the discrete-time H∞ model matching problem with integral control are proven. The controller synthesis theorem and the controller design algorithm is elaborated in order to minimize the H∞ norm of the closed-loop transfer function and to maximize the closed-loop performance by introducing the model transfer matrix. In following, the discrete-time H∞ MMP via LMI approach is derived as the main result. The controller construction procedure is implemented by using a well-known toolbox to improve the usability of the presented results. Finally, some conclusions are given.

scholarly journals A SIMPLE FIVE-STEP METHODOLOGY TO DETERMINE CONTROLLABILITY OF HEAT EXCHANGER NETWORKS USING STEADY-STATE INFORMATION

2011 ◽  
Author(s):  
Rodolfo Tellez ◽  
William Y. Svrcek ◽  
Brent R. Young
Keyword(s):  
Steady State ◽  
Heat Exchanger ◽  
Process Integration ◽  
Plant Design ◽  
State Information ◽  
Step Procedure ◽  
Heat Exchanger Networks ◽  
Propose Control Strategy ◽  
Optimum Heat ◽  
And Control

Process integration design methodologies have been developed and introduced to synthesise an optimum heat exchanger network (HEN) arrangement. However, controllability issues are often overlooked during the early stages of a plant design. In this paper we present a five-step procedure that involves the use of multivariable disturbance and control analyses based solely on steady-state information and with the purpose to assess process design developments and to propose control strategy alternatives appropriate and suitable for a HEN.

A Novel Approach for Business Process Model Matching Using Genetic Algorithms

2020 ◽  
Vol 12 (1) ◽  
pp. 1-19
Author(s):  
Mostefai Abdelkader ◽  
Ignacio García Rodríguez de Guzmán
Keyword(s):  
Genetic Algorithms ◽  
Business Process ◽  
Process Model ◽  
Optimization Problem ◽  
Process Models ◽  
Similarity Metrics ◽  
Model Matching ◽  
Matching Problem ◽  
Novel Approach ◽  
The One

This paper formulates the process model matching problem as an optimization problem and presents a heuristic approach based on genetic algorithms for computing a good enough alignment. An alignment is a set of not overlapping correspondences (i.e., pairs) between two process models(i.e., BP) and each correspondence is a pair of two sets of activities that represent the same behavior. The first set belongs to a source BP and the second set to a target BP. The proposed approach computes the solution by searching, over all possible alignments, the one that maximizes the intra-pairs cohesion while minimizing inter-pairs coupling. Cohesion of pairs and coupling between them is assessed using a proposed heuristic that combines syntactic and semantic similarity metrics. The proposed approach was evaluated on three well-known datasets. The results of the experiment showed that the approach has the potential to match business process models effectively.

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