基于完全启动系统方法的四旋翼无人机信息收集跟踪任务的全面重建和预测控制
1Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin 150001, China.
ISA transactions
|January 27, 2024
概括
本研究提出了一种用于控制四旋翼无人机 (UAV) 收集信息的新方法. 该方法重建无人机模型以简化复杂的控制问题,实现实时性能.
科学领域:
- 机器人技术 机器人技术 机器人技术
- 控制系统工程 控制系统工程
- 航空航天工程 航空航天工程
背景情况:
- 四旋翼无人驾驶飞行器 (UAV) 存在复杂的控制挑战,原因是低启动和混合制约.
- 现有的预测控制 (PC) 方法与四旋翼系统固有的非线性和相互依赖性作斗争.
- 信息收集任务需要无人机的强大和高效的控制策略.
研究的目的:
- 为四旋翼无人机开发一种全新的全动力系统 (FAS) 预测控制 (PC) 框架.
- 将系统模型重建,混合约束处理和性能指数优化集成到统一的控制方案中.
- 提高四旋翼无人机在信息收集任务期间的实时性能和稳定性.
主要方法:
- 重建低功率四旋翼无人机模型,将其改造成完全功率系统 (FAS) 模型.
- 从模型重建中产生的隐性混合约束的明确转换和解.
- 开发一个级联预测算法,解决时间变化的输入约束,并将非线性优化解为线性凸问题.
- 通过仔细选择预测参数来确保闭环稳定性.
主要成果:
- 在四旋翼无人机模型中成功注入了全启动特性.
- 通过减少系统复杂性,非线性和相互依赖,显著降低了计算需求.
- 通过解优化问题实现了令人满意的实时性能.
- 验证了跟踪错误闭环系统的稳定性.
结论:
- 拟议的FAS-PC方法有效地解决了四旋翼无人机用于信息收集的控制复杂性.
- 该方法展示了强大的性能和稳定性,通过模拟和实际飞行任务进行验证.
- 这种新的框架为先进的无人机控制应用提供了计算效率高,可靠的解决方案.
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