Performance portrait method: Robust design of predictive integral controller
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Súbory
Dátum
2025
Názov časopisu
ISSN časopisu
Názov zväzku
Vydavateľ
Multidisciplinary Digital Publishing Institute : Basel
ISBN
ISSN
2313-7673
Abstrakt
The performance portrait method (PPM) can be characterized as a systematized digitalized version of the trial and error method—probably the most popular and very often used method of engineering work. Its digitization required the expansion of performance measures used to evaluate the step responses of dynamic systems. Based on process modeling, PPM also contributed to the classification of models describing linear and non-linear dynamic processes so that they approximate their dynamics using the smallest possible number of numerical parameters. From most bio-inspired procedures of artificial intelligence and optimization used for the design of automatic controllers, PPM is distinguished by the possibility of repeated application of once generated performance portraits (PPs). These represent information about the process obtained by evaluating the performance of setpoint and disturbance step responses for all relevant values of the determining loop parameters organized into a grid. It can be supported by the implementation of parallel calculations with optimized decomposition in the high-performance computing (HPC) cloud. The wide applicability of PPM ranges from verification of analytically calculated optimal settings achieved by various approaches to controller design, to the analysis as well as optimal and robust setting of controllers for processes where other known control design methods fail. One such situation is illustrated by an example of predictive integrating (PrI) controller design for processes with a dominant time-delayed sensor dynamics, representing a counterpart of proportional-integrating (PI) controllers, the most frequently used solutions in practice. PrI controllers can be considered as a generalization of the disturbance–response feedback—the oldest known method for the design of dead-time compensators by Reswick. In applications with dominant dead-time and loop time constants located in the feedback (sensors), as those, e.g., met in magnetoencephalography (MEG), it makes it possible to significantly improve the control performance. PPM shows that, despite the absence of effective analytical control design methods for such situations, it is possible to obtain high-quality optimal solutions for processes that require working with uncertain models specified by interval parameters, while achieving invariance to changes in uncertain parameters.
Popis
In: Biomimetics. Basel : Multidisciplinary Digital Publishing Institute, 2025. ISSN 2313-7673. Vol. 10, no. 2 (2025), pp. 1-30.
Kľúčové slová
optimálne riadenie, integračné perspektívy, meranie kvality, princíp správania sa
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Citácia
Práva a licenčné podmienky
CC BY Creative Commons Attribution 4.0. International
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess