Genetic Algorithm is a search heuristic that mimics the process of evaluation. Genetic Algorithms can be applied to process controllers for their optimization using natural operators. This paper discusses the concept and design procedure of Genetic Algorithm as an optimization tool. Further, this paper explores the well established methodologies of the literature to realize the workability and applicability of genetic algorithms for process control applications. Genetic Algorithms are applied to direct torque control of induction motor drive, speed control of gas turbine, speed control of DC servo motor for the optimization of control parameters in this work. The simulations were carried out in simulink package of MATLAB. The simulation results show better optimization of hybrid genetic algorithm controllers than fuzzy standalone and conventional controllers.

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A typical thermal power plant operated using 70–80% gram straw, 10–15% cotton straw, 5–10% wheat straw and leaves (2%) with a small quantity of coal (1–2%) as fuel mixture, produces a residue called Biomass-Based Thermal Power Plant Fly Ash (BBTPFS)

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