Biomedical Engineering Reference
In-Depth Information
Table 4 Comparison of results
Tuning method
Rise time (s)
Maximum overshot
Settling time (s)
Ziegler Nichols
0.18
1.08
2.41
Genetic algorithm
0.161
1.01
0.7
Conclusion
The GA algorithm for PID controller tuning presented in this research offers
several advantages. The errors resulting from model reduction are avoided. It is
possible to consider several design criteria in a balanced and unified way.
Approximations that are typical to classical tuning rules are not needed. Soft
computing techniques are often criticized for two reasons: algorithms are com-
putationally heavy and convergence to the optimal solution cannot be guaranteed.
PID controller tuning is a small-scale problem and thus computational complexity
is not really an issue here. It took only a couple of seconds to solve the problem.
Compared to conventionally tuned system, GA tuned system has good steady-state
response and performance indices.
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