Thota K. Radhakrishnan

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The aim of this paper is to implement controllers based on soft computing techniques in real time for a non-linear process. The process taken up for study is to control the level in a conical tank setup using cost effective data acquisition system. The system identification of this non-linear process is done using black box modeling and found to be First(More)
Nonlinearities present in the systems make their controller design a non-trivial task. The difficulty further increases in case of multi-input–multi-output (MIMO) systems with increased number of variables and interactions between them. In this paper, fuzzy based intelligent control schemes are designed for control of nonlinear single-input–single-output(More)
Most of the large and complex industrial processes are naturally Multi Input Multi Output systems. Compared with single-input single-output (SISO) counterparts, MIMO systems are more complex to control due to inherent nonlinearity and due to the existence of interactions among input and output variables. Control of nonlinear MIMO process is a challenging(More)
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