An improved particle swarm optimization （PSO） algorithm is investigated in the optimization of the attitude controller parameters of unmanned aerial vehicle （UAV）. Considering the stagnation phenomenon in the late...An improved particle swarm optimization （PSO） algorithm is investigated in the optimization of the attitude controller parameters of unmanned aerial vehicle （UAV）. Considering the stagnation phenomenon in the later phase of the basic PSO algorithm caused by the diversity scarcity of particles, a modified PSO algorithm is presented. For the basic PSO algorithm, the velocity of each particle is adjusted according to the inertia motion, the swarm previous best position and its own previous best position. However, in the improved PSO algorithm, each particle only learns from another randomly selected particle with higher performance, besides keeping the inertia motion. The inertia weight of the improved PSO algorithm is a random number. The modification decreases the uncertain parameters of the algorithm, simplifies the learning mechanism of the particle, and enhances the diversity of the swarm. Furthermore, a UAV attitude control system is built, and the improved PSO algorithm is applied in the optimized tuning of four controller parameters. Simulation results show that the improved PSO algorithm has stronger global searching ability than the common PSO algorithms, and obtains better UAV attitude control parameters.展开更多
In this study,an ultra‐fast and simple solvent‐free microwave method was successfully demonstrated using a series of ultra‐small(~2.5 nm)surfactant‐free Ru_(2)P@Ru/CNT heterostructures for the first time.The struc...In this study,an ultra‐fast and simple solvent‐free microwave method was successfully demonstrated using a series of ultra‐small(~2.5 nm)surfactant‐free Ru_(2)P@Ru/CNT heterostructures for the first time.The structure has a high‐density Ru component and Ru_(2)P component interface,which accelerates the hydrogen evolution reaction(HER).The prepared Ru_(2)P@Ru/CNT demonstrated excellent catalytic effects for the HER in alkaline media and real seawater.The experimental results indicate that ratio‐optimized Ru_(2)P@Ru/CNT(Ru_(2)P:Ru=66:34)requires only 23 and 29 mV to reach 10 mA cm^(-2)in 1.0 mol/L KOH and real seawater,respectively.These values are 10 and 24 mV lower than those of commercial Pt/C in 1.0 mol/L KOH(33 mV)and real seawater(53 mV),respectively,making it among the best non‐Pt HER reported in the literature.Additionally,the TOF of Ru_(2)P@Ru/CNT in alkaline freshwater and seawater were 13.1 and 8.5 s^(-1),respectively.These exceed the corresponding values for Pt/C,indicating that the catalyst has excellent intrinsic activity.The high current activity of Ru_(2)P@Ru/CNT in 1.0 mol/L KOH was explored,and only 77 and 104 mV were required to reach 500 and 1000 mA cm^(-2),respectively.After 100 h of durability testing,the catalyst retained excellent catalytic and structural stability in low current density,high current density,and seawater.展开更多
基金Supported by the Graduate Student Research Innovation Program of Jiangsu Province(CX08B-091Z)the Innovation and Excellence Foundation of Doctoral Dissertation of Nanjing University of Aeronautics and Astronautics(BCXJ08-06)~~
文摘An improved particle swarm optimization （PSO） algorithm is investigated in the optimization of the attitude controller parameters of unmanned aerial vehicle （UAV）. Considering the stagnation phenomenon in the later phase of the basic PSO algorithm caused by the diversity scarcity of particles, a modified PSO algorithm is presented. For the basic PSO algorithm, the velocity of each particle is adjusted according to the inertia motion, the swarm previous best position and its own previous best position. However, in the improved PSO algorithm, each particle only learns from another randomly selected particle with higher performance, besides keeping the inertia motion. The inertia weight of the improved PSO algorithm is a random number. The modification decreases the uncertain parameters of the algorithm, simplifies the learning mechanism of the particle, and enhances the diversity of the swarm. Furthermore, a UAV attitude control system is built, and the improved PSO algorithm is applied in the optimized tuning of four controller parameters. Simulation results show that the improved PSO algorithm has stronger global searching ability than the common PSO algorithms, and obtains better UAV attitude control parameters.
文摘In this study,an ultra‐fast and simple solvent‐free microwave method was successfully demonstrated using a series of ultra‐small(~2.5 nm)surfactant‐free Ru_(2)P@Ru/CNT heterostructures for the first time.The structure has a high‐density Ru component and Ru_(2)P component interface,which accelerates the hydrogen evolution reaction(HER).The prepared Ru_(2)P@Ru/CNT demonstrated excellent catalytic effects for the HER in alkaline media and real seawater.The experimental results indicate that ratio‐optimized Ru_(2)P@Ru/CNT(Ru_(2)P:Ru=66:34)requires only 23 and 29 mV to reach 10 mA cm^(-2)in 1.0 mol/L KOH and real seawater,respectively.These values are 10 and 24 mV lower than those of commercial Pt/C in 1.0 mol/L KOH(33 mV)and real seawater(53 mV),respectively,making it among the best non‐Pt HER reported in the literature.Additionally,the TOF of Ru_(2)P@Ru/CNT in alkaline freshwater and seawater were 13.1 and 8.5 s^(-1),respectively.These exceed the corresponding values for Pt/C,indicating that the catalyst has excellent intrinsic activity.The high current activity of Ru_(2)P@Ru/CNT in 1.0 mol/L KOH was explored,and only 77 and 104 mV were required to reach 500 and 1000 mA cm^(-2),respectively.After 100 h of durability testing,the catalyst retained excellent catalytic and structural stability in low current density,high current density,and seawater.
