摘要
通过对微小型水下潜航器的建模,针对微小型水下潜航器自动定向、自动定深和定高,以及速度在内的一些参数提出了改进控制结构和底层控制的方法。针对自动定深、定高、定位等水平面控制,改进串级双闭环控制结构,提高了控制的响应速度和调节精度。通过传统PID控制、利用粒子群算法(PSO)进行参数优化的改进PID控制以及模糊控制3种控制方法,分析微小型水下无人潜航器在底层控制方面的优劣。仿真对比发现,粒子群优化的PID(PSO-PID)算法的控制效果在速度控制方面明显强于普通PID算法,但由于微小型水下潜航器数学模型的不确定性,在位置控制方面弱于模糊控制器,证明了所提出的方法具有快速动态响应特性,并具有一定的鲁棒性,拥有较高的控制性能。
Based on the modeling of micro autonomous underwater vehicle,a modified control structure and an improved low-level control method are proposed for some parameters,such as automatic orientation,automatic depth,height and speed of micro autonomous underwater vehicle.The double closed-loop control structure is improved to increase the response speed and the adjustment precision for the control parameters.Analyze the advantages and disadvantages of the micro autonomous underwater vehicle in the low-level control by three control method—the digital PID control,the improved PID control using particle swarm optimization(PSO)to optimize parameters and fuzzy control.Compared with the general PID algorithm,the particle swarm optimization PID(PSO-PID)presents much better on speed control.However,due to the uncertainty of the mathematical model of the micro autonomous underwater vehicle,its performance on position control is weaker than the fuzzy controller.The simulation results show that the proposed method presents fast dynamic response,certain robustness and high control performance.
出处
《中国科技论文》
北大核心
2017年第14期1602-1609,共8页
China Sciencepaper
基金
国家自然科学基金资助项目(51579047)
黑龙江省自然科学基金资助项目(QC2017048)
毫米波国家重点实验室开放课题(K201707)
关键词
控制科学与控制工程
微小型水下潜航器
粒子群算法
PID控制
模糊控制
底层控制
control science and control engineering
micro underwater vehicle
particle swarm optimization algorithm
piD control
fuzzy control
low-level control technology