Design and tuning of standard additive model based fuzzy PID controllers for multivariable process systems.
This paper describes a design and two-level tuning method for fuzzy proportional-integral derivative (FPID) controllers for a multivariable process where the fuzzy inference uses the inference of standard additive model. The proposed method can be used for any n x n multi-input-multi-output process and guarantees closed-loop stability. In the two-level tuning scheme, the tuning follows two steps: low-level tuning followed by high-level tuning. The low-level tuning adjusts apparent linear gains, whereas the high-level tuning changes the nonlinearity in the normalized fuzzy output. In this paper, two types of FPID configurations are considered, and their performances are evaluated by using a real-time multizone temperature control problem having a 3 x 3 process system.
Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, BC V6T 1Z4, Canada. eranda@ece.ubc.ca
Eranda
E
Harinath
George K I
GK
Mann
D000465:Algorithms; D003198:Computer Simulation; D005246:Feedback; D017143:Fuzzy Logic; D015233:Models, Statistical; D015999:Multivariate Analysis