Design and Tuning of Parallel Distributed Compensation-based Fuzzy Logic Controller for Temperature

Snejana Yordanova^1, and Yavor Sivchev¹

¹Faculty of Automation, Technical University of Sofia, Sofia, Bulgaria

Cite this paper:
Snejana Yordanova and Yavor Sivchev. Design and Tuning of Parallel Distributed Compensation-based Fuzzy Logic Controller for Temperature. Journal of Automation and Control. 2014; 2(3):79-85. doi: 10.12691/automation-2-3-3

Abstract

The parallel distributed compensation (PDC) gains popularity in designing of simple fuzzy logic controllers (FLCs) for nonlinear plants taking advantage of the well-developed linear control theory. The established design approaches suffer difficulties in derivation of standard TSK plant models for processes characterized by time delays, model uncertainties, nonlinearities, inertia, etc., needed for the PDC design. The standard PDC structure is also unfit for parameter optimization and embedding in programmable logic controllers which ensures a broad industrial application. The aim of the investigation is to develop an approach for the design and tuning of a modified process PI PDC-FLC and an on-line fuzzy logic supervisor via off-line GA optimization techniques in order to ensure closed loop stability, robustness, desired performance and energy efficiency. The approach is developed on the example of air temperature control in a laboratory dryer using MATLAB^TM. Simulations and real time control shows a decreased settling time and increased system robustness and energy efficiency compared to linear PI control.

Keywords:
fuzzy logic supervisor genetic algorithms process parallel distributed compensation temperature real time control tsk models

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