Sadhana K. Chidrawar

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An efficient implementation of Generalized Predictive Control using multi-layer feed forward neural network as the plant’s nonlinear model is presented. Two algorithm i.e. Newton Raphson and Levenberg Marquardt algorithm are implemented and their results are compared. The details about this implementation are given. The utility of each algorithm is(More)
The brain is a highly specialized organ. It serves as the control center for functions of the body and allows us to cope with our environment. Based on biological theory of human brain, artificial neural network are models that attempt to parallel and simulate the functionality and decision making processes of human brain. In general neural network is(More)
This paper is focused on issues of process modeling and model based control strategy of chemical reactor process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into optimal supersaturating trajectory. It is achieved by; manipulating coolant flow rate, the influent concentration of compound is(More)
In this paper Hybrid Direct Neural Controller (HDNC) with Linear Feedback Compensator (LFBC) has been developed. Proper initialization of neural network weights is a critical problem. This paper presents two different neural network configurations with unity and random weight initialization while using it as a direct controller and linear feedback(More)
  • Sanket Lokhande, Akshay Bhaskarwar, +13 authors Thomer M. Gil
  • 2012
This paper focuses on theoretical and practical methods for detecting bandwidth attacks upon networks and sites. Comparison of existing methods used in traditional networks, as well as discussion of a new method for detecting attacks is presented. Advantages and limitations of few of methods are considered. Attack Detection helps to plan a security(More)
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