Hybrid modelling of a sugar boiling process

Abstract

Abstract:The first and maybe the most important step in designing a model-based predictive controller is to develop a model that is as accurate as possible and that is valid under a wide range of operating conditions. The sugar boiling process is a strongly nonlinear and nonstationary process. The main process nonlinearities are represented by the crystal growth rate. This paper addresses the development of the crystal growth rate model according to two approaches. The first approach is classical and consists of determining the parameters of the empirical expressions of the growth rate through the use of a nonlinear programming optimization technique. The second is a novel modeling strategy that combines an artificial neural network (ANN) as an approximator of the growth rate with prior knowledge represented by the mass balance of sucrose crystals. The first results show that the first type of model performs local fitting while the second offers a greater flexibility. The two models were developed with industrial data collected from a 60 m 3 batch evaporative crystallizer.

Hybrid semi-parametric modeling in process systems engineering: Past, present and future

“…The focus in this section is on modeling applications that deal with experimental data rather than data from virtual, simulated experiments, because simulation cases are typically applied to validate a pro-posed methodology (methodologies have been discussed above), while experimental studies are much more practically oriented. It can be seen in (Bhutani et al, 2006;Feil et al, 2004;Fiedler & Schuppert, 2008;Hinchliffe, Montague, Willis, & Burke, 2003;Mogk et al, 2002;Tian et al, 2001;Tsen et al, 1996;Vega, Lima, & Pinto, 2000), crystallization (Georgieva & de Azevedo, 2009;Georgieva, Meireles, & Feyo de Azevedo, 2003;Lauret, Boyer, & Gatina, 2000), metallurgic processes (Hu et al, 2011;Jia, Mao, Chang, & Zhao, 2011;Reuter et al, 1993;Sohlberg, 2005), distilla-tion columns (Chen et al, 2004;Mahalec & Sanchez, 2012;Safavi, Nooraii, & Romagnoli, 1999), drying processes (Cubillos & Acuna, 2007), thermal devices (Arahal, Cirre, & Berenguel, 2008), mechan-ical reactors (Nascimento et al, 1999) or milling (Aguiar & Filho, 2001; Kumar Akkisetty, Lee, Reklaitis, & Venkatasubramanian, 2010), for more details and references see Table2 -supplementary material. Since the number of applications is relatively large and most of which either use the standard serial approach consisting of material and/or energy balances in which the kinetics are represented by a nonparametric model or a parallel approach, only some approaches are discussed here, namely those that present solutions of more complex problems.…”

“…Particle size distribution, which is of major interest in many processes, can be modeled with population balances, as for instance in crystallization (Georgieva et al, 2003;Hermanto, Braatz, & Chiu, 2011;Lauret et al, 2000;Zhang, Wang, He, & Jia, 2012), milling (Kumar Akkisetty et al, 2010) or polymerization (Doyle et al, 2003). The application of a complementary nonparametric model, e.g.…”

Nonlinear predictive control based on artificial neural network model for industrial crystallization

“…A wide variety of mathematical models can be found in the scientific literature to describe these HMT, both steady state (Semlali Aouragh Hassani et al, 2001) and dynamic models (Lauret et al, 2000;Georgieva et al, 2003). A widely used dynamic model derives from nine ordinary differential equations, including the population balance represented by four moment equations (Eqs.…”

Dynamic Optimisation of Industrial Sugar Crystallization Process based on a Hybrid (mechanistic+ANN) Model

“…subject to: equations (1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11) Several methods can tackle the optimisation problem (32). The derivative based deterministic methods are rather sensitive to the model initial conditions and do not guarantee a global optimum but they are faster than the stochastic methods and are usually more appropriate to on-line optimisation.…”