A uncultivated wolf pack algorithm for high-dimensional functions and its application in parameters optimization of PID controller

To solve high-dimensional function optimization problems, many swarm intelligent algorithms have been proposed. Inspired by hunting behavior and distribution mode of uncultivated and barbarous wolf pack, we proposed a method, named uncultivated wolf pack algorithm (UWPA). Experiments are conducted on a suit of high-dimensional benchmark functions with different characteristics. What´s more, the compared simulation experiments with other three typical intelligent algorithms, show that UWPA has better convergence and robustness. At last, this algorithm is successfully applied in parameters searching for PID controller.