optimization of FOPID Controller Based on MPFGA

As an extension of traditional proportional-integral-derivative (PID) in the fractional order field, fractional order proportional-integral-derivative (FOPID) controller has a better dynamic performance and anti-interference performance. This paper proposes a multiple population fuzzy genetic algorithm (MPFGA) to optimize the operating parameters of FOPID controller. According to the diversity and evolution of populations, this algorithm is adopted to optimize the crossover probability $(P_{c})$ and mutation probability $(P_{m})$ by the strategy of fuzzy logic and multiple population to improve the convergent efficiency and perfect premature convergence. The simulation results indicate that FOPID controller based on MPFGA has short adjustment time, small static error, strong anti-interference ability and steady-state performance.