The design of fractional-order PID control of a Boost converter is studied, and the fractional-order inductor and capacitor models of the system are fitted using the Oustaloup filter approximation algorithm. To solve the problems of insufficient learning capability and weak iterative convergence when a particle swarm optimization (PSO) algorithm is used to adjust the parameters of the fractional-order PID controller, an improved PSO algorithm is proposed, which introduces three strategies of adaptive inertia weight, adaptive learning factor and weighted mutation to improve the diversity of particles and enhance the convergence speed and accuracy. The improved PSO algorithm is applied to the design of a PID control system for a fractional-order Boost converter. Simulation results show that the control system designed using the improved PSO algorithm has a faster dynamic response of output voltage and inductance current, a better anti-interference capability of output voltage and a better tracking and adjusting capability of inductance current when the load changes suddenly.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |