Self-tuning temperature control of a polymerizing reactor

Design and implementation of a fuzzy supervisor for on-line compensation of nonlinearities: An instability avoidance module

“…Some non-fuzzy based variable gain tuning methods are an Adaptive PI algorithm (Ali, 2000), a Self-Tuning PID by Adaptive Interaction (Lin et al, 2000), an Adaptive/SelfTuning PID by Frequency Loop-Shaping (Grassi et al, 2000), a Self-Tuning PID using a Genetic Algorithm (Mitsukura et al, 1999), and a Self-Tuning PID based on a Generalized Minimum Variance Control (GMVC) Law (Yamamoto et al, 1998). Even though the previous methods demonstrate good performance in the published application it will be difficult to implement them in an industrial control problem.…”

Steady-State Tracking Properties for the Generalized Minimum Variance Controller: A Review, Proportional-Integral-Derivative Tuning, and Applications

“…Popular early works that have implemented the GMV characteristic in the PID design are Cameron and Seborg (1983) 27 and Yamamoto et al (1998). 28 Table 3 describes the main properties of each control synthesis (the parameter ν is related to the proportional gain K c ). Successful performance of the GMV-PID controller is observed with quick response, smooth transients, and small control variance in the presence of the nonlinear nature of the plant.…”

“…Popular early works that have implemented the GMV characteristic in the PID design are Cameron and Seborg (1983) and Yamamoto et al (1998) . Table describes the main properties of each control synthesis (the parameter ν is related to the proportional gain K c ).…”