Abstract:The water level in boiler drum is the critical control parameter to be addressed for providing the efficient and safe operation of steam generators in power plants. The regulation is achieved by using the Artificial Intelligence (AI) technique, namely, Adaptive Neuro-Fuzzy Inference System (ANFIS). It has the capability of self-learning as ANN with the linguistic expression function of fuzzy inference, whose membership functions and fuzzy rules are acquired from a large lot of existing data instead of experience. So, it is well renowned for its control performance in the power system area due to the nonlinear nature and robustness to system parameters uncertainties in multidisciplinary domains and power system too. Here, ANFIS controller takes the error and change of error in water level as inputs to control the actuator of inflow water such that the steam flow out of the steam generator meets the requirement of turbine unit set point which indirectly resembles the demanded load by the Generation System Operator (GSO). The performance of the proposed ANFIS controller is analyzed in terms of tracking the water level set point of boiler drum. For this purpose, a boiler model is developed using the MATLAB/SIMULINK working platform. Then, the proposed ANFIS controller is designed and tested on it for water level regulation. The simulation results are examined and compared with existing FIS technique.
A boiler system is an integral component of a sugar plant and control of water level in the drum of the boiler is a critical operational consideration. Nowadays, instead of conventional control techniques, modern control techniques have been implemented for a lot of industrial models practically or theoretically. In this paper, we describe the effectiveness of LabVIEW in order to provide better drum level control of various products evolved in a sugarcane industry.
This paper deals with the position control of robot arm for material handling in product based manufacturing industries. The robot arm is designed using two DC servo motors coupled with quadrature encoder which provides mobility with two degrees of freedom. The end effector of the arm is a core and coil arrangement which is used to pick and place materials at desired position. PID controller is developed to position the servo motor at required angle based on material location and activates the end effector to handle the material. The controller is designed in embedded FPGA architecture of National Instruments CompactRIO (NI cRIO-9073) and interfaced with motors through NI 9505 DC servo drive modules. The speed and resolution of position control is high due to on-board 40MHz clock frequency and parallel execution of logical blocks in RIO FPGA. CompactRIO is programmed with NI LabVIEW graphical programming tool which minimizes the programming complexity.Keyword s -FPGA, PID controller, robot arm, servo motor, pick and place I.
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