Fuzzy Multivariable Control Strategy Applied to a Refrigeration System
| Autor: | Jones Erni Schmitz, Flávio Vasconcelos da Silva, Ivan Carlos Franco, Ana Maria Frattini Fileti, Saulo Fernando dos Santos Vidal |
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| Rok vydání: | 2016 |
| Předmět: |
Computer science
020209 energy General Chemical Engineering Multivariable calculus Control (management) Refrigeration Control engineering 02 engineering and technology Energy consumption Fuzzy logic 020401 chemical engineering Control theory Modeling and Simulation 0202 electrical engineering electronic engineering information engineering 0204 chemical engineering |
| Zdroj: | Chemical Product and Process Modeling. 12 |
| ISSN: | 1934-2659 2194-6159 |
| DOI: | 10.1515/cppm-2016-0033 |
| Popis: | The refrigeration process involves complex systems exhibiting nonlinearities and coupled behavior, so this paper aims to evaluate the comparative performance of a multivariable fuzzy logic-based control system and a classic multi loop PID. The process variables were the temperature of the secondary fluid (propylene glycol) outlet and the evaporating temperature. The manipulated variables were the compressor frequency speed and the pump frequency speed. Aspen Plus and Aspen Dynamics simulators were used to simulate the experimental prototype. The model was previously validated and linked with MATLAB software, where the controllers were implemented. Tuning of the fuzzy controller was performed through the membership functions and gains adjustments. The tuning of the multi loop PID controller was performed using the Ziegler-Nichols method and then a fine tuning was carried out. In order to fairly compare energy consumption and control effort, the tune of PID-based strategy was finished when similar values of Integral of Squared Error were achieved. Thus, very similar behavior for the process variables in both controllers. On the other hand, a great improvement in the control effort and energy saving was observed when the multivariable fuzzy controller was used in comparison to classic PID. The energy consumption was reduced by 25 % and the control effort by 96 % when the proposed strategy was used. |
| Databáze: | OpenAIRE |
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