Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Cluster analysis & Control theory. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

Design of Fractional Order PID controller for liquid level control of spherical tank

Abstract: In this paper, Fractional Order Proportional Integral Derivative Controller (FOPID) is designed for liquid level control of a spherical tank which is modeled as a First Order Plus Dead Time (FOPDT) system about an operating point. The response of designed FOPID controller is compared with the traditional integer order PID (IOPID) controller in simulation and with IOPI controller on experimental setup. The PIλDμ controller is designed using minimization of Integral Square Error (ISE) method. This method offers a practical and systematic way of the controllers design for the considered class of FOPDT plant. From the simulation and experimental results presented, the designed fractional order controller works efficiently with improved performance comparing with the integer order controller.

Dynamic resource allocation with optimized task scheduling and improved power management in cloud computing

Abstract: Cloud computing is one among the emerging platforms in business, IT enterprise and mobile computing applications. Resources like Software, CPU, Memory and I/O devices etc. are utilized and charged as per the usage, instead of buying it. A Proper and efficient resource allocation in this dynamic cloud environment becomes the challenging task due to drastic increment in cloud usage. Various promising technologies have been developed to improve the efficiency of resource allocation process. But still there is some incompetency in terms of task scheduling and power consumption, when the system gets overloaded. So an energy efficient task scheduling algorithm is required to improve the efficiency of resource allocation process. In this paper an improved task scheduling and an optimal power minimization approach is proposed for efficient dynamic resource allocation process. Using prediction mechanism and dynamic resource table updating algorithm, efficiency of resource allocation in terms of task completion and response time is achieved. This framework brings an efficient result in terms of power reduction since it reduces the power consumption in data centers. The proposed approach gives accurate values for updating resource table. An efficient resource allocation is achieved by an improved task scheduling technique and reduced power consumption approach. The Simulation result gives 8% better results when comparing to other existing methods.