An Improved Particle Swarm Optimization Algorithm for Fractional Order PID Parameter Tuning

Chaobo Chen

Abstract


An improved particle swarm optimization algorithm is proposed to tune the parameters of fractional order PID controller in this paper. The fitness function is set based on the performance index of the system in time domain. In the process of iteration, partial particles are re-initialized when they evolved slower than the others. Meanwhile, the adaptive inertia weight value is adopted to get the optimal solution by globally searching. Finally, applying the proposed fractional PID controller into a typical servo control system, the simulation results indicate that the parameter tuning method based on improved particle swarm optimization has better convergence speed. The control system with fractional PID algorithm has better performance-short adjusting time, fast rising velocity, strong anti-jamming capability, at the same time, this fractional PID controller could be better than standard particle swarm optimization algorithm and genetic algorithm.


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References


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