Fuzzy control of a neutralization process
Engineering Applications of Artificial Intelligence
Modeling and control of a pilot pH plant using genetic algorithm
Engineering Applications of Artificial Intelligence
Brief Parallel structure and tuning of a fuzzy PID controller
Automatica (Journal of IFAC)
Brief MIMO fuzzy internal model control
Automatica (Journal of IFAC)
Differential Evolution Based Fuzzy Logic Controller for Nonlinear Process Control
Fundamenta Informaticae
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Although a fuzzy logic controller is generally nonlinear, a PI-type fuzzy controller that uses only control error and change in control error is not able to detect the process nonlinearity and make a control move accordingly. In this paper, a multiregion fuzzy logic controller is proposed for nonlinear process control. Based on prior knowledge, the process to be controlled is divided into fuzzy regions such as high-gain, low-gain, large-time-constant, and small-time-constant. Then a fuzzy controller is designed based on the regional information. Using an auxiliary process variable to detect the process operating regions, the resulting multiregion fuzzy logic controller can give satisfactory performance in all regions. Rule combination and controller tuning are discussed. Application of the controller to pH control is demonstrated