Title :
Design and implementation of fuzzy based robust controller for process control instrumentation
Author :
Akshay, Naregalkar
Author_Institution :
Dept. of Electron. & Instrum. Eng., VNR Vignana Jyothi Inst. of Eng. & Technol., Hyderabad, India
Abstract :
Precised and robust controllers are need of Industries like Chemical, Petrochemical plants which required to operate with the defined parameters and unknown disturbances. Therefore a robust controller is required to maintain process parameters. Conventional PID Controller tuning requires lot of mathematical hard work. Though, mathematical controllers are easy to implement, but are not précised one. Also, the tuned parameters of PID Controller for a particular setup will not be optimum when the system physical parameter is changed, then the controller should be robust to overcome such scenario. An approximate mathematical controller for real time applications requires complex considerations. Previous knowledge on system characteristic equation as PID controller is not required while implementing Fuzzy Logic Controller. Fuzzy Logic Controller based on theory of approximate mathematical reasoning enables to treat decisively and precisely. This paper focuses on design and implementation of fuzzy based control to utilize human intelligence and reasoning. The fuzzy logic control is implemented using Fuzzy Logic Toolkit in LabVIEW software and tested with Process Control temperature and level loops. Data Acquisition is done using NI cFP AIO-610 with NI cFP-2020 PAC modules.
Keywords :
chemical industry; control engineering computing; data acquisition; fuzzy control; petrochemicals; process control; production engineering computing; robust control; virtual instrumentation; LabVIEW software; NI cFP AIO-610 module; NI cFP-2020 PAC module; chemical plants; data acquisition; fuzzy based robust controller; fuzzy logic control; fuzzy logic toolkit; human intelligence; human reasoning; level loops; petrochemical plants; process control instrumentation; process control temperature; Fuzzy logic; Instruments; Mathematical model; Process control; Robustness; Transfer functions; Valves; Fuzzy logic; LabVIEW; PID; Robust controller; process control Instrumentation;
Conference_Titel :
Convergence of Technology (I2CT), 2014 International Conference for
Print_ISBN :
978-1-4799-3758-5
DOI :
10.1109/I2CT.2014.7092084