INVESTIGATION ON METAHEURISTIC ALGORITHMS FOR OPTIMIZING FRACTIONAL ORDER CONTROLLER PARAMETERS (International Journal of Food and Nutritional Sciences, 2022)
Optimization problems are of prime importance for industrial as well as the scientific community in diversedisciplines. There are various optimization problems that present traits like high non-linearity .and multimodality, the solutionof which is usually complex. Further, in many cases, some intricate optimization problems present noise and/ordiscontinuities which make conventional deterministic methods inefficient to obtain global solutions. Thus, globaloptimization approaches based on metaheuristics provide a viable alternative for solving complex optimization problems anddo not require any information regarding the properties of the objective function. Metaheuristic algorithms are nowadaysattaining popularity among researchers extensively owing to their success to find the optimum solution and steadfastness insolving real-world problems. They are generally utilized to solve several complex problems in science and engineering, financeas well as management. Metaheuristic algorithms have four inherent properties. First of all, they are primarily motivated bynatural phenomena in the universe. Secondly, they constitute a stochastic method wherein an optimum solution is notguaranteed and is randomly searched in a feasible search space. Moreover, they do not require the derivative term to obtainthe maximum or the minimum value. Last but not the least; they are always associated with some user-defined values at theinitial stage to function suitably. Therefore this work gives the detail review on metaheuristic algorithms for optimizingfractional order controller parameters.