FPGA–implementation of PID-controller by differential evolution optimization

Mika Hanhila, Timo Mantere, Jarmo T. Alander
2018 Open Engineering  
We will describe an FPGA implementation of PID-controller that uses differential evolution to optimize the coefficients of the PID controller, which has been implemented in VHDL. The original differential evolution algorithm was improved by ranking based mutation operation and self-adaptation of mutation and crossover parameters. Ranking-based mutation operation improves the quality of solution, convergence rate and success of optimization. Due to the self-adaptive control parameters, the user
more » ... oes not have to estimate the mutation and crossover rates. Optimization have been performed by calculating for each generation fitness value by means of trial parameters. The final optimal parameters are selected based on the minimum fitness.
doi:10.1515/eng-2018-0038 fatcat:ypg5qyq5zbb5jbmoe2umy6n3ti