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The Artificial Bee Colony or ABC is one of the newest additions to the class of Nature Inspired Algorithms (NIA) mimicking the foraging behavior of honey bees. In ABC, the food locations represent the potential candidate solution. In the present study an attempt is made to generate the population of food sources (Colony Size) adaptively with the help of proposed algorithm ABC-SAC (artificial bee colony...
In this paper, improved differential evolution (IDE) algorithm with variable 'del' parameter is presented. Recently developed IDE algorithm is used for global optimization of non-linear complex problems. The 'del' parameter is a predetermined level of tolerance for predefined allowable number of iterations which triggers the different mutation schemes in restart mechanism phase of IDE algorithm. The...
This paper presents improved differential evolution (IDE) algorithm with variable dynamic non-linear increased crossover rate. The IDE algorithm is proposed recently with dynamic nonlinear increased crossover rate for global optimization of nonlinear functions. In variable dynamic nonlinear increased crossover rate, the parameter k is made variable in the range [1,10]. The proposed algorithm is tested...
This paper presents an efficient and fast tuning method of controller parameters for position control of DC servo motor. A control scheme for PID controller tuning is proposed here which is based on Luus-Jaakola Optimization. Luus-Jaakola optimization procedure is used to optimize large scale nonlinear optimization problems. The tuning of PID controllers is accomplished by minimizing the Integral-Square-Error...
In this contribution, PID controller is designed for position control of DC servo-motor using Integral-Square-Error (ISE) minimization. The ISE to be minimized is first written in terms of alpha and beta coefficients. This formulation of ISE requires only fixed numbers of alpha and beta coefficients in contrast to conventional formulation of ISE in which integration upto infinite time is needed. The...
Differential Evolution (DE) is a popular technique for solving real parameter global optimization problems. Several variants of DE are proposed in literature which aims at further strengthening its performance for solving complex problems. In the present study we suggest a simple and efficient modification in the selection strategy of basic DE. The proposed strategy is named Information Preserving...
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