Porównanie różnych sposobów optymalizacji nastaw regulacji procesów przemysłowych z uwzględnieniem wpływu wskaźników oceny ich jakości

pol Artykuł w języku polskim DOI: 10.14313/PAR_233/27

Konrad Bogusz , Bartosz Rajkowski , wyślij Paweł D. Domański Politechnika Warszawska, Instytut Automatyki i Informatyki Stosowanej

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Streszczenie

Jakość regulacji jest kluczowym zagadnieniem w nowoczesnym przemyśle. Zadaniem inżyniera jest nie tylko dobór parametrów regulacji, ale również bieżące nadzorowanie jej jakości tak, aby maksymalizować wydajność procesu a także dbać o stan aparatury i urządzeń wykonawczych. W zdecydowanej większości rozwiązań praktycznych stosowany jest kwadratowy wskaźnik jakości, zarówno w procesie strojenia jak i oceny jakości regulacji. W artykule zostały zaproponowane inne wskaźniki, cechujące się większą odpornością. Zostały one zastosowane do dwóch zadań: projektowania nastaw regulatora oraz oceny jakości już pracującej struktury sterowania. W pracy uwzględnione zostały rozwiązania dla różnych wersji podstawowego algorytmu regulacji w przemyśle procesowym, tj. PID. Różne strategie regulacji PID zostały również porównane z algorytmem sterowania predykcyjnego typu MPC. Analiza symulacyjna wykorzystuje przemysłowy benchmark układu sterowania systemem chłodniczym wykorzystującym zjawisko kompresji pary.

Słowa kluczowe

analiza R/S, MPC, ocena jakości sterowania, pid, wykładnik Hursta

Comparison of Various Controller Parameters Optimization Strategies for Industrial Processes Using Different Control Performance Assessment Indexes

Abstract

Control quality is a crucial issue in modern industry. The engineer’s goal is to set control parameters and assess it constantly in order to maximize the efficiency of the process and watch the condition of actuators. The article describes a number of Control Performance Assessment indexes. They are applied to two tasks: controller tuning and the assessment of the quality of an already tuned control strategy. It presents a comparison between different indexes applied to various structures of the PID control algorithm. Finally the results are compared with Model Predictive Control. The analysis uses well known nonlinear industrial benchmark of a refrigeration system based on vapour compression.

Keywords

Control Performance Assessment, Hurst exponent, MPC, pid, R/S analysis

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