R. B. Gopaluni

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Alarmingly low pulp prices in early 2009 left pulp and paper mills across North America desperate for any way to improve thin profit margins. One solution that continues to gain popularity among the industry is improved energy management systems for cogeneration systems, which use steam for two purposes - to provide heat for the pulping process, and to(More)
Abnormal functioning of different organs such as pancreas, liver and/or body tissues can result in excessive blood glucose concentration in type II diabetic patients. Although a number of models have been developed for evaluating type I diabetes mellitus, there is limited evaluation for patients with type II. This paper presents the development of a model(More)
We propose a novel model-based algorithm for fault detection in nonlinear and non-Gaussian systems. The algorithm utilizes particle filters to generate a sequence of hidden states, which are then used in a log-likelihood ratio test to detect faults. The state-space models considered in this article are not easily amenable to standard log-likelihood ratio(More)
We adapt the maximum likelihood method to treat symmetric noncausal models. Such models govern the cross-directional response of paper machines: they are noncausal in space, not in time. Process symmetry is essential to our methods. We show that every symmetric noncausal process admits a spectrally equivalent causal model, then prove that the maximum(More)
The nonlinear stochastic systems pose two important challenges in designing alarms: 1) measurements are not necessarily Gaussian distributed and 2) measurements are correlated - in particular for closed loop systems. We present an algorithm for designing alarms for such systems with unknown and known models. In the case of unknown models our approach is(More)
In this work, we have extended the current success of deep learning and reinforcement learning to process control problems. We have shown that if reward hypothesis functions are formulated properly, they can be used for industrial process control. The controller setup follows the typical reinforcement learning setup, whereby an agent (controller) interacts(More)
We utilize the particle filter algorithm to develop a fault isolation approach based on general observer scheme (GOS) in nonlinear and non-Gaussian systems. The proposed fault isolation scheme is based on a set of parallel particle filters each sensitive to all faults except one. The performance of the proposed approach is compared to an alternative(More)
Type II diabetes mellitus is characterized by several abnormalities in different body organs such as the pancreas, the liver, muscles and adipose tissues. We have developed a technique to detect the dysfunction of different organs in a group of type II diabetic patients. The detection of these abnormalities is performed through euglycemic insulin clamp and(More)
Controlling blood glucose level for patient with type 2 diabetes mellitus (T2DM) has been influenced by many variables with significant levels of variability, such as insulin sensitivity, carbohydrates intake, exercise, and more. These variabilities make controlling blood glucose level a complex problem. In patients with advanced T2DM, when the body fails(More)
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