PID Controller Tuning Using Soft Computing Techniques - Proceedings of All India Seminar on Biomedical Engineering 2012 (AISOBE-2012) - page 270

Table 3 Parameters of GA

GA property Value/method

Population size 80

Fitness function MSE

Selection method Geometric selection

Crossover method Arithmetic

Number of crossover points 3

Mutation method Uniform mutation

Mutation probability 0.01

Fig. 5 Position control using
genetic algorithm

Fig. 6 Comparison of GA
and ZN technique

Analysis of Result

All the conventional methods of controller tuning lead to a large settling time,
overshoot, rise time, and steady-state error of the controlled system. Hence a soft
computing techniques are introduced into the control loop. GA-based tuning
methods have proved their excellence in giving better results by improving the
steady-state characteristics and performance indices (Fig. 6 , Table 4 ).