| 引用本文: | 张国庆,姚明启,杨婷婷,张卫东.考虑事件触发输入的船舶自适应动力定位控制[J].控制理论与应用,2021,38(10):1597~1606.[点击复制] |
| ZHANG Guo-qing,YAO Ming-qi,YANG Ting-ting,ZHANG Wei-dong.Adaptive dynamic positioning control for ships with event-triggered input[J].Control Theory and Technology,2021,38(10):1597~1606.[点击复制] |
|
| 考虑事件触发输入的船舶自适应动力定位控制 |
| Adaptive dynamic positioning control for ships with event-triggered input |
| 摘要点击 1883 全文点击 509 投稿时间：2020-07-06 修订日期：2021-08-30 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2021.00416 |
| 2021,38(10):1597-1606 |
| 中文关键词 动力定位 事件触发控制 鲁棒神经阻尼 增益不确定 自适应控制 |
| 英文关键词 dynamic positioning event-triggered control robust neural damping gain uncertainty adaptive control |
| 基金项目 国家自然科学基金项目(51909018, 52171291), 辽宁省自然科学基金机器人联合基金项目(20180520039), 大连市科技创新基金项目(2019J12 GX026), 中央高校基本科研业务费专项资金项目(3132021132, 3132021340)资助. |
|
| 中文摘要 |
| 为解决实际海况下全驱动船舶的动力定位控制任务存在参数不确定、模型结构不确定和通信资源限制等
问题, 本文提出一种具有事件触发输入的鲁棒自适应动力定位控制算法. 该算法采用径向基函数神经网络对系统模
型不确定进行逼近, 同时针对通信带宽受限问题, 设计了一种具有事件触发机制的执行器输入, 降低了控制器和执
行器之间的信道占用. 此外, 该算法还解决了状态变量与执行器增益不确定性之间的强耦合问题, 并且设计了在线
更新的自适应参数去补偿执行器增益不确定, 以确保船舶能够稳定执行动力定位任务. 利用Lyapunov稳定性理论证
明了闭环控制系统中所有误差变量都满足半全局一致最终有界收敛. 通过对比仿真实验验证了所提出算法的有效
性. |
| 英文摘要 |
| This paper focuses on proposing a robust adaptive dynamic positioning control algorithm with event-triggered
input to deal with the parameters uncertainty, model structure uncertainty and the constraints of communication resource
under the practical marine environment. The radial basic function neural networks are utilized to approximate the system
uncertainty. And the actuator inputs with event-triggered mechanism are designed to reduce the occupation of communication
channel in the presence of communication bandwidth limitation. Furthermore, the problem of strong couplings
between the actuator gain uncertainties and the state variables is solved and the adaptive parameters are derived to compensate
the gain uncertainty of actuators online. The Lyapunov theory is employed to prove that all error signals satisfy the
semi-global uniform ultimate bounded stability. Finally, the effectiveness of the proposed algorithm is validated through
the comparative simulation experiments. |
|
|
|
|
|