Symbolic to genetic tuning of PID controllers

Genetic algorithms (GAs) are optimization techniques inspired from natural genetics. A genetic algorithm has in view to evaluate many points in the parameter space with the aim to converge to the global optimal solution. Mathematica software is an excellent symbolic tool for hard tasks and is used in this paper. Proportional Integral Derivative (PID) control is very important for the quality of robust control, new approaches as symbolic to genetic tuning of PID Controllers are excellent choice to solve this problem. A global integral index ISE (Integral of Squared Error) is minimized. At first the PID Symbolic Tuning is considered. The complicated problem of robust genetic tuning is solved. Some examples obtained by simulation are considered in both cases.