The Conventional control approach may not be suitable for non-linear systems and for the systems with considerable parameter variations over a period of time. On the other hand adaptive control techniques proved to be a convenient tool in dealing with the above said systems. The Model Reference Adaptive Systems (MRAS) with performance specifications given in terms of reference model is tried fo...

Local learning based soft sensing methods are effective in dealing with process nonlinearities as well as time varying characteristics. In this paper, an anti-over-fitting method is proposed for appropriate online local model adaptation. The proposed method is based on the weighted sum of the predicted errors for the newest few samples, the weights of which are determined adaptively. Moreover, ...

Simulation is the technical discipline which shows the behavior and reactions of any system on its model. Most processes in nature have nonlinear properties and simulation is one way to examine behaviour of these systems. The behaviour is then obtained by steady-state and dynamic analysis of the model which is usually represented by a set of differential equations. The next step after dynamic a...

The development of a Self-Tuning Neuro-Fuzzy Generalized Minimum Variance (GMV) controller is described. It uses fuzzy expert knowledge of the dynamic weightings to meet desired closed-loop stability and performance requirements. The controller is formulated in a polynomial system approach mixed with a Neuro-Fuzzy model and Fuzzy Self-Tuning mechanism. The proposed method is applied to a model ...

In this work, a novel stirred tank for the production of H2 by the biological fermentation of organic wastes is presented. The bioreactor design must ensure effective mixing of the liquid phase, full contact between the substrate and the biofilm and energy efficient biogas recovery. A vortexingesting dual impeller stirred vessel equipped with a central draft tube containing the packing support ...

Bovine serum albumin (BSA) was applied as a model non-catalytic protein to enzymatic hydrolysis of Avicel and dilute acid pretreated corn stover at different reaction conditions to improve the understanding of its ability to enhance cellulose hydrolysis. Addition of BSA improved the 72 h hydrolysis yields in shake flasks by up to 26% for both substrates by reducing de-activation of the exogluca...

Model Predictive Control (MPC) refers to a class of algorithms that compute a sequence of manipulated variable adjustments in order to optimize the future behaviour of a plant. MPC technology can now be found in a wide variety of application areas. The neural network predictive controller that is discussed in this paper uses a neural network model of a nonlinear plant to predict future plant pe...

The ‘eng-genes’ concept, in which system-related nonlinearities are used as hidden-layer activation functions, has proven effective in the context of nonlinear systems modelling. This concept is now extended to control applications. An eng-genes network is integrated into a nonlinear adaptive controller and applied to a simulation of the Continuous Stirred Tank Reactor (CSTR), an application wi...

We discuss the stabilization of a class of nonlinear systems describing the dynamics of a stirred tank chemical reactor. The stabilization is achieved using linear dynamic feedback. Several types of controllers are defined for which closed loop global asymptotic stability of the set point can be proved. We also discuss the case where the closed loop possesses several equilibrium states and the ...

This paper proposes a strategy for feature extraction and classification of high dimensional noisy data. Firstly, the moving median filter is used for reducing the effect of noise and outliers in the measurement data. Then, the data is projected to a lower dimension feature space using radial basis function (RBF) network and polygonal line. It is integrated with learning vector quantization (LV...