Application of Hierarchical Neural Fuzzy Models to Modeling and Control of a Bioprocess
نویسندگان
چکیده
Hierarchical structures have been introduced in the literature to deal with the dimensionality problem which is the main drawback to the application of neural networks and fuzzy models to modeling and control of largescale systems. In the present work, hierarchical neural fuzzy (HNF) models are reviewed focusing on the modelbased control of a biotechnological process. The model considered here consists of a set of neural fuzzy systems connected in cascade and is used in the modeling of an industrial plant for ethyl alcohol (ethanol) production. Based on the HNF model of the process, a nonlinear model predictive controller (HNF-MPC) is designed and applied to control the process. The performance of the HNF-MPC is illustrated within servo and regulatory scenarios.
منابع مشابه
Forecasting Gold Price Changes: Application of an Equipped Artificial Neural Network
The forecast of fluctuations and prices is the major concern in financial markets. Thus, developing an accurate and robust forecasting decision model is critically favorable to the investors. As gold has shown a special capability to smooth inflation fluctuations, governors use gold as a price controlling lever. Thus, more information about future gold price trends will help to make the firm de...
متن کاملDecentralized Adaptive Fuzzy-Neural Control of an Anaerobic Digestion Bioprocess Plant
The paper proposed to use recurrent Fuzzy-Neural Multi-Model (FNMM) identifier for decentralized identification of a distributed parameter anaerobic wastewater treatment digestion bioprocess, carried out in a fixed bed and a recirculation tank. The distributed parameter analytical model of the digestion bioprocess is used as a plant data generator. It is reduced to a lumped system using the ort...
متن کاملReview and Classification of Modeling Approaches of Soil Hydrology Processes
To use soil hydrology processe (SHP) models, which have increasingly extended during the last years, comprehensive knowledge about these models and their modeling approaches seems to be necessary. The modeling approaches can be categorized as either classical or non-classical. Classical approaches mainly model the SHP through solving the general unsaturated flow (Richards) equation, numerically...
متن کاملReview and Classification of Modeling Approaches of Soil Hydrology Processes
To use soil hydrology processes (SHP) models, which have increasingly extended during the last years, comprehensive knowledge about these models and their modeling approaches seems to be necessary. The modeling approaches can be categorized as either classical or non-classical. Classical approaches mainly model the SHP through solving the general unsaturated flow (Richards) equation, numericall...
متن کاملGyroscope Random Drift Modeling, using Neural Networks, Fuzzy Neural and Traditional Time- series Methods
In this paper statistical and time series models are used for determining the random drift of a dynamically Tuned Gyroscope (DTG). This drift is compensated with optimal predictive transfer function. Also nonlinear neural-network and fuzzy-neural models are investigated for prediction and compensation of the random drift. Finally the different models are compared together and their advantages a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Applied Artificial Intelligence
دوره 20 شماره
صفحات -
تاریخ انتشار 2006