动力定位船舶鲁棒自适应异步自触发控制
Robust adaptive asynchronous self-triggered control of dynamic positioning ships
姚明启 1张国庆 1宋纯羽 1张显库1
作者信息
- 1. 大连海事大学 航海学院,辽宁 大连 116026
- 折叠
摘要
针对动力定位船舶的通信带宽受限、执行器增益不确定性等问题,本文提出了一种异步自触发动力定位控制策略.该策略设计了一种自触发机制,解决了传统事件触发方法需要对触发条件进行连续监控这一约束,即下一触发时刻仅需要根据当前时刻的相关信息进行计算.对于具有多个执行器的动力定位船舶,每个执行器的自触发机制相互独立互不影响,即其每个控制器-执行器信道中的控制信号均为异步触发式传输.此外,对于每个执行器设计了一个自适应参数对其增益不确定性进行在线估计和补偿.通过仿真实验对上述控制策略进行验证,仿真结果表明:所提出算法具有较高的定位精度与稳定性能,且极大程度上减少了控制信号的传输次数,相较于对比算法减少了 100 倍传输次数,具有低通信负载的优点,更加符合工程需求.
Abstract
This paper presents an asynchronous self-triggered control strategy to address the challenges of communi-cation bandwidth limitations and actuator gain uncertainty in dynamic positioning ships.We introduce a novel self-triggered mechanism that overcomes the need for continuous monitoring required by conventional event-triggered methods.This mechanism calculates the next triggered instant merely depending on the current information.For a dynamic positioning ship equipped with multiple actuators,our self-triggering mechanism allows each actuator to operate independently and without interaction.This means that control signals are transmitted in an asynchronous self-triggered transmission mode in each controller-actuator communication channel.Furthermore,we have devel-oped an adaptive parameter for each actuator to estimate and compensate for its gain uncertainty through the control-ler online.The above control strategies have been verified by simulation experiments.The simulation results show that our proposed algorithm achieves high positioning accuracy and stable performance while also reducing the fre-quency of control signal transmissions to a great extent.Compared with a contrastive algorithm,our method a-chieves a 100-fold reduction in transmission times,thereby considerably lowering the low communication load.This makes it well-suited to engineering requirements.
关键词
动力定位/自触发控制/增益不确定/自适应控制/鲁棒控制/神经网络/反步法/非线性控制Key words
dynamic positioning/self-triggered control/gain uncertainty/adaptive control/robust control/neural network/backstepping/nonlinear control引用本文复制引用
基金项目
国家自然科学基金项目(52171291)
辽宁省应用基础研究计划项目(2023JH2/101600039)
辽宁省"兴辽英才计划"青年拔尖人才(XLYC2203129)
大连市杰出青年科技人才项目(2022RJ07)
大连市重点领域创新团队支持计划(2020RT08)
中央高校基本科研业务费专项资金项目(3132023137)
中央高校基本科研业务费专项资金项目(3132023502)
出版年
2024
国家科技期刊平台
NSTL
万方数据