Optimal robust controller based on adaptive parallel genetic algorithms in uncertain domain
Bugong Xu · Control theory & applications · 2012
In most of the existing robust controller designs based on the genetic algorithm,the search domains of variable are factitiously assigned.For undefined search domains,we propose a novel method for designing the optimal robust controller based on the adaptive parallel genetic algorithm.According to the distribution of the best individuals of each population in the current search,the algorithm narrows the uncertain search domain of variables by using the probability and statistics theory,so as to gradually achieve the optimum.Moreover,the impact of the individual fitness on the crossover probability and mutation probability is also investigated.By using this method,we design a simple,proper and low-order optimal robust controller,which effectively avoids the local optimum and improves the convergence and accuracy in simulation experiments.