Modeling and control of a pilot pH plant using genetic algorithm

Modeling and validation of nonlinear time-varying pH industrial processes

“…All weak solutions have the ability to resist changes in pH. This ability it is called buffering [5].…”

A two-stage intelligent optimization system for the raw slurry preparing process of alumina sintering production

“…Though an adaptive method is proposed for cement raw material blending (Bá nyá sz et al, 2003), it is difficult to identify the process model of the RSPP from the input and output measurements due to the difficulty of online measurement. Alternatively, intelligent methods, like expert systems, neural networks (NNs) and genetic algorithms (GAs), have been used for optimal control of blending problems (Wang et al, 2006;Wen et al, 2004;Yang et al, 2008aYang et al, , 2000 and other complex industrial processes (Linkens and Chen, 1995;Tan et al, 2005;Xiong and Zhang, 2004) owing to their capability to emulate the behavior of human expert and to model the complex system. Therefore, the intelligent method is a good candidate for the optimal control of raw material proportioning in alumina production.…”

Adaptive nonlinear control of pH neutralization processes using fuzzy approximators

“…Kalafatis, Wang, and Cluett (2005) have used the Wiener model and feedforward technique for pH control. Tan, Lu, Loh, and Tan (2005) have also employed a Wiener model-based controller to regulate the pH level of a weak-acid strong-base neutralization process.…”