CN115047763A - 一种多无人机系统的最小能量控制方法 - Google Patents
一种多无人机系统的最小能量控制方法 Download PDFInfo
- Publication number
- CN115047763A CN115047763A CN202210639228.XA CN202210639228A CN115047763A CN 115047763 A CN115047763 A CN 115047763A CN 202210639228 A CN202210639228 A CN 202210639228A CN 115047763 A CN115047763 A CN 115047763A
- Authority
- CN
- China
- Prior art keywords
- point
- unmanned aerial
- aerial vehicle
- iterative learning
- control
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000005457 optimization Methods 0.000 claims abstract description 57
- 239000011159 matrix material Substances 0.000 claims abstract description 38
- 238000009826 distribution Methods 0.000 claims abstract description 36
- 238000011480 coordinate descent method Methods 0.000 claims abstract description 18
- 238000013461 design Methods 0.000 claims abstract description 13
- 230000006870 function Effects 0.000 claims description 26
- 238000005070 sampling Methods 0.000 claims description 11
- 230000009466 transformation Effects 0.000 claims description 8
- 239000013598 vector Substances 0.000 claims description 8
- 238000012546 transfer Methods 0.000 claims description 6
- 238000004891 communication Methods 0.000 claims description 5
- 230000008859 change Effects 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 238000006073 displacement reaction Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 3
- 230000003190 augmentative effect Effects 0.000 claims description 2
- 238000010923 batch production Methods 0.000 claims description 2
- 238000000605 extraction Methods 0.000 claims description 2
- 230000003252 repetitive effect Effects 0.000 claims description 2
- 238000006467 substitution reaction Methods 0.000 claims description 2
- 238000005265 energy consumption Methods 0.000 abstract 1
- 238000005516 engineering process Methods 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 9
- 238000006243 chemical reaction Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000003750 conditioning effect Effects 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Evolutionary Computation (AREA)
- Medical Informatics (AREA)
- Software Systems (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
Description
Claims (1)
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210639228.XA CN115047763B (zh) | 2022-06-08 | 2022-06-08 | 一种多无人机系统的最小能量控制方法 |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202210639228.XA CN115047763B (zh) | 2022-06-08 | 2022-06-08 | 一种多无人机系统的最小能量控制方法 |
Publications (2)
Publication Number | Publication Date |
---|---|
CN115047763A true CN115047763A (zh) | 2022-09-13 |
CN115047763B CN115047763B (zh) | 2023-10-13 |
Family
ID=83161556
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202210639228.XA Active CN115047763B (zh) | 2022-06-08 | 2022-06-08 | 一种多无人机系统的最小能量控制方法 |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN115047763B (zh) |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116893619A (zh) * | 2023-08-29 | 2023-10-17 | 江南大学 | 一种工业机器人量化迭代学习控制方法 |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140188273A1 (en) * | 2012-12-31 | 2014-07-03 | King Fahd University Of Petroleum And Minerals | Control method for mobile parallel manipulators |
CN110262543A (zh) * | 2019-05-23 | 2019-09-20 | 北京航空航天大学 | 多目标点同时到达约束下的集群四维轨迹规划设计方法 |
CN110815225A (zh) * | 2019-11-15 | 2020-02-21 | 江南大学 | 电机驱动单机械臂系统的点对点迭代学习优化控制方法 |
CN113341726A (zh) * | 2021-06-18 | 2021-09-03 | 江南大学 | 一种多质点车辆队列行驶系统的迭代学习控制方法 |
CN113900377A (zh) * | 2021-10-19 | 2022-01-07 | 江南大学 | 双转子气动系统点对点迭代学习最小能量控制方法 |
WO2022088471A1 (zh) * | 2020-10-28 | 2022-05-05 | 江南大学 | 一种移动机器人变批次长度迭代学习优化控制方法 |
-
2022
- 2022-06-08 CN CN202210639228.XA patent/CN115047763B/zh active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20140188273A1 (en) * | 2012-12-31 | 2014-07-03 | King Fahd University Of Petroleum And Minerals | Control method for mobile parallel manipulators |
CN110262543A (zh) * | 2019-05-23 | 2019-09-20 | 北京航空航天大学 | 多目标点同时到达约束下的集群四维轨迹规划设计方法 |
CN110815225A (zh) * | 2019-11-15 | 2020-02-21 | 江南大学 | 电机驱动单机械臂系统的点对点迭代学习优化控制方法 |
WO2022088471A1 (zh) * | 2020-10-28 | 2022-05-05 | 江南大学 | 一种移动机器人变批次长度迭代学习优化控制方法 |
CN113341726A (zh) * | 2021-06-18 | 2021-09-03 | 江南大学 | 一种多质点车辆队列行驶系统的迭代学习控制方法 |
CN113900377A (zh) * | 2021-10-19 | 2022-01-07 | 江南大学 | 双转子气动系统点对点迭代学习最小能量控制方法 |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116893619A (zh) * | 2023-08-29 | 2023-10-17 | 江南大学 | 一种工业机器人量化迭代学习控制方法 |
CN116893619B (zh) * | 2023-08-29 | 2024-04-09 | 江南大学 | 一种工业机器人量化迭代学习控制方法 |
Also Published As
Publication number | Publication date |
---|---|
CN115047763B (zh) | 2023-10-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Cheng et al. | Real-time optimal control for spacecraft orbit transfer via multiscale deep neural networks | |
Asif et al. | Adaptive sliding mode dynamic controller with integrator in the loop for nonholonomic wheeled mobile robot trajectory tracking | |
Peng et al. | Distributed model reference adaptive control for cooperative tracking of uncertain dynamical multi‐agent systems | |
Hao et al. | Adaptive dynamic surface control for cooperative path following of underactuated marine surface vehicles via fast learning | |
CN110815225B (zh) | 电机驱动单机械臂系统的点对点迭代学习优化控制方法 | |
Xiong et al. | Model-free adaptive control for unknown MIMO nonaffine nonlinear discrete-time systems with experimental validation | |
CN112318505B (zh) | 一种移动机器人变批次长度迭代学习优化控制方法 | |
Karg et al. | Deep learning-based embedded mixed-integer model predictive control | |
Kingravi et al. | Reproducing kernel Hilbert space approach for the online update of radial bases in neuro-adaptive control | |
Qi et al. | Stable indirect adaptive control based on discrete-time T–S fuzzy model | |
Wang et al. | Distributed consensus protocols for coordinated control of multiple quadrotors under a directed topology | |
Yang et al. | Superior robustness of power-sum activation functions in Zhang neural networks for time-varying quadratic programs perturbed with large implementation errors | |
You et al. | Comprehensive design of uniform robust exact disturbance observer and fixed‐time controller for reusable launch vehicles | |
Xiong et al. | Fixed‐time observer based adaptive neural network time‐varying formation tracking control for multi‐agent systems via minimal learning parameter approach | |
de Almeida et al. | Real-time minimum snap trajectory generation for quadcopters: Algorithm speed-up through machine learning | |
Wang et al. | Neural network‐based multivariable fixed‐time terminal sliding mode control for re‐entry vehicles | |
CN115047763A (zh) | 一种多无人机系统的最小能量控制方法 | |
Ji et al. | Optimal consensus model-free control for multi-agent systems subject to input delays and switching topologies | |
Xu et al. | Adaptive sliding mode disturbance observer–based funnel trajectory tracking control of quadrotor with external disturbances | |
CN117055605A (zh) | 多无人机姿态控制方法及系统 | |
CN113900377B (zh) | 双转子气动系统点对点迭代学习最小能量控制方法 | |
Cui et al. | Finite‐time trajectory tracking control for autonomous airships with uncertainties and external disturbances | |
Che et al. | Data‐driven model‐free adaptive attitude control for morphing vehicles | |
CN107480381B (zh) | 基于模拟退火算法构建响应面模型的方法及应用其的系统 | |
Ma et al. | Adaptive neural network control of a non‐linear two‐degree‐of‐freedom helicopter system with prescribed performance |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
TA01 | Transfer of patent application right |
Effective date of registration: 20230914 Address after: Room 05, 27th Floor, Building 1, Phase 3, Guannan Fuxing Pharmaceutical Park, No. 58 Guanggu Avenue, Donghu New Technology Development Zone, Wuhan City, Hubei Province, 430000 (Wuhan Area of Free Trade Zone) Applicant after: Wuhan Tianzhiran Intellectual Property Operation Co.,Ltd. Address before: 214100 7th floor, South Building, No. 898, Tongsha Road, Liangxi District, Wuxi City, Jiangsu Province Applicant before: Jiangnan University Effective date of registration: 20230914 Address after: 239300 North of Guangling Road, east of Erfeng South Road, Tianchang City, Chuzhou City, Anhui Province Applicant after: TIANCHANG CITY POWER SUPPLY COMPANY OF STATE GRID ANHUI POWER CO.,LTD. Applicant after: STATE GRID ANHUI POWER CO., LTD. CHUZHOU POWER SUPPLY Co. Applicant after: Chuzhou Dongyuan Electric Power Engineering Co.,Ltd. Tianchang Branch Address before: Room 05, 27th Floor, Building 1, Phase 3, Guannan Fuxing Pharmaceutical Park, No. 58 Guanggu Avenue, Donghu New Technology Development Zone, Wuhan City, Hubei Province, 430000 (Wuhan Area of Free Trade Zone) Applicant before: Wuhan Tianzhiran Intellectual Property Operation Co.,Ltd. |
|
TA01 | Transfer of patent application right | ||
GR01 | Patent grant | ||
GR01 | Patent grant |