.png){kind=icon}
返回
Sampling-Optimization-Based Adaptive Formation Tracking With Trajectory Protection
.png){kind=icon}
PRE
AI
DOI：10.1109/JSYST.2023.3305358.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This article studies an adaptive formation tracking problem with trajectory protection. The adaptive formation tracking problem for each sampling tracking point is transformed into a distributed constrained optimization problem. A distributed-optimization-based strategy is proposed to search for the optimal formation configuration. Considering the trajectory protection, some auxiliary variables are transmitted directly in the communication process of the multiagent system rather than the sensitive information, i.e., the sampling tracking point. Interestingly, before the achievement of the optimal formation configuration, the information of the sampling tracking point will not be disclosed, even though the eavesdropper is omnipotent, and meanwhile, the accuracy of tracking is not influenced. Then, a sampling-optimization-based adaptive formation tracking with trajectory protection (SOAFT-TP) algorithm is proposed to achieve adaptive formation tracking in the obstacle-existence environment with trajectory protection. It modifies the formation configuration adaptively to respond to the real-time environment by updating the constraint parameters online. Finally, the theoretical results of the SOAFT-TP algorithm are verified by a simulation example.
Keyword:
Adaptive formation tracking
distributed-optimization-based strategy
sampling-optimization-based adaptive formation tracking with trajectory protection (SOAFT-TP) algorithm
trajectory protection
期刊
I
IF:
2.4
论文数:
4.5K
被引数:
387
机构
引用论文
分享收藏Uncertain Multiagent Systems With Distributed Constrained Optimization Missions and Event-Triggered Communications: Application to Resource Allocation具有分布式约束优化任务和事件触发通信的不确定多主体系统: 在资源分配中的应用
OAAI
OAAI分享收藏Affine formation maneuver control of high-order multi-agent systems over directed networks.png)
AUTOMATICA
AUTOMATICAIF5.9
PREAI
分享收藏Distributed Continuous-Time Convex Optimization With Time-Varying Cost Functions具有时变成本函数的分布式连续时间凸优化
OAAI
OAAI分享收藏Optimal Tracking Control of Nonlinear Multiagent Systems Using Internal Reinforce Q-Learning基于内部强化Q学习的非线性多智能体系统最优跟踪控制
PREAI
分享收藏Finite-Time Velocity-Free Rendezvous Control of Multiple AUV Systems With Intermittent Communication
PREAI
分享收藏
查看更多内容