Estimation of Biomass Enzymatic Hydrolysis State in Stirred Tank Reactor through Moving Horizon Algorithms with Fixed and Dynamic Fuzzy Weights

Abstract

Second generation ethanol faces challenges before profitable implementation. Biomass hydrolysis is one of the bottlenecks, especially when this process occurs at high solids loading and with enzymatic catalysts. Under this setting, kinetic modeling and reaction monitoring are hindered due to the conditions of the medium, while increasing the mixing power. An algorithm that addresses these challenges might improve the reactor performance. In this work, a soft sensor that is based on agitation power measurements that uses an Artificial Neural Network (ANN) as an internal model is proposed in order to predict free carbohydrates concentrations. The developed soft sensor is used in a Moving Horizon Estimator (MHE) algorithm to improve the prediction of state variables during biomass hydrolysis. The algorithm is developed and used for batch and fed-batch hydrolysis experimental runs. An alteration of the classical MHE is proposed for improving prediction, using a novel fuzzy rule to alter the filter weights online. This alteration improved the prediction when compared to the original MHE in both training data sets (tracking error decreased 13%) and in test data sets, where the error reduction obtained is 44%.

Challenges and Opportunities on Nonlinear State Estimation of Chemical and Biochemical Processes

“…Hybrid methods combine two or more estimation technologies, either as part of an integrated framework or to perform different tasks in the estimation procedure. Examples of the latter are the use of AI-based methods to describe the process dynamics (modeling task), combined with Bayesian algorithms to carry out the estimation task, taking into account the stochastic nature of the system [14,[53][54][55]. On the other hand, integrated frameworks considering, for instance, EKF/PF-MHE may use time-efficient technologies, such as EKF and PF, to obtain fast state estimates between MHE optimizations, which are robust to bad priors and unmodeled disturbances [13,17,36].…”

“…A considerable amount of literature has been published on the development and application of state estimators to improve monitoring of chemical [3][4][5][6][7][8][9][10] and biochemical [11][12][13][14] processes. Previous research and review articles have also covered state estimation aspects in terms of classification [1,15,16], design, and applications [1,17,18], as well as challenges and trends on nonlinear state estimation [1,16,19,20].…”

“…To highlight the performance and computational time challenges of nonlinear state estimation methods, a case study involving the implementation of EKF and MHE is performed considering the nonlinear case study from reference [128]. This case study consists of a batch reactor model considering the reaction mechanism shown below in Equations ( 10) and ( 11) and the corresponding system of differential equations in Equations ( 12)- (14).…”

Special Issue on “Bioenergy Systems, Material Management, and Sustainability”

“…This Special Issue, "Bioenergy Systems, Material Management, and Sustainability", encompasses a combination of contributed articles by a diverse set of worldwide experts in the Americas, Europe, and Asia, focusing on a multitude of concepts and topics. The following topics, along with the manuscript contributions, are addressed in this issue: Bio-based materials and processes [1,2], bioenergy systems optimization, advanced control for sustainability and state estimation [3][4][5][6][7], sustainability, life cycle assessment, and life cycle inventory analyses associated with biosystems and biofuels [8][9][10], sustainable management and valorization of organic/biomass waste, including energy production [11,12], and techno-economic analysis of novel routes for the sustainable utilization and reuse of biomass and waste [13]. Such topics are of great interest and critical relevance to the sustainable development of local, regional, national, and international communities.…”