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Observation-Driven Multiple UAV coordinated Standoff Target tracking Based on Model Predictive Control

Tsinghua Science and Technology 2022年第6期27卷 948-963页

作者： Shun Sun Yu Liu Shaojun Guo Gang Li Xiaohu Yuan Department of Control Science and Technology Naval Aviation UniversityYantai 264001China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China National Institute of Defense Technology Innovation Academy of Military Sciences PLABeijing 100091China Department of Automation Tsinghua UniversityBeijing 100084China

An observation-driven method for coordinated standoff target tracking based on Model Predictive Control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering over a target.After acquiring a fusion estimate of the target state,each UAV locally measures the observation capability of the entire UAV system with the Fisher Information Matrix(FIM)determinant in the decentralized architecture.To facilitate observation optimization,only the FIM determinant is adopted to derive the performance function and control constraints for coordinated standoff tracking.Additionally,a modified iterative scheme is introduced to improve the iterative efficiency,and a consistent circular direction control is established to maintain long-term observation performance when the UAV approaches its target.Sufficient experiments with simulated and real trajectories validate that the proposed method can improve observation of the UAV system for target tracking and adaptively optimize UAV trajectories according to sensor performance and UAV-target geometry.

关键词： coordinated tracking standoff tracking observation-driven Model Predictive Control(MPC) multiple UAVs Fisher Information Matrix(FIM)

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A coordinated tracking Control of Multi-Agent Systems Using Data-Driven Methods

A Coordinated Tracking Control of Multi-Agent Systems Using ...

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第37届中国控制会议

作者： You Wu Guo-Ping Liu School of Information Science and Engineering Central South University School of Engineering University of South Wales CTGT Center Harbin Institute of Technology

This paper presents a coordinated tracking control scheme of multi-agent systems（MAS） based on a data-driven approach.Each agent uses the golden section adaptive control as one of the data-driven methods to realize intelligent self-adaptive,and is able to quickly respond to the changing given target.Several proportional,integral and derivative（PID）controllers are applied as the coordinated controller along with improved adjacent coupling structure,simpler coordination structure and better synchronization performance are accomplished.The consensus and stability of closed-loop MAS using the proposed control scheme is analyzed by using a kind of necessary and sufficient conditions.Validity and feasibility of the coordinated tracking control scheme of MAS is verified by simulation examples.

关键词： Multi-Agent Systems Golden Section Adaptive Control Adjacent Coupling coordinated tracking

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Attitude coordinated tracking for Formation Spacecraft under a Directed Graph

Attitude Coordinated Tracking for Formation Spacecraft under...

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第三十届中国控制会议

作者： ZHANG Haibo,MEI Jie,MA Guangfu Department of Control Science and Engineering,Harbin Institute of Technology,Heilongjiang 150001,P.R.China

In this paper we study the attitude coordinated tracking problem for formation spacecraft under a directed graph. We design a distributed coordinated tracking algorithm which guarantees all followers to track the leader.It is shown that the closed system is asymptotically stable as long as the directed communication topology characterizing the interaction among the followers and the leader contains a directed spanning tree.Then,we extend the distributed control algorithm to guarantee that the spacecraft maintain constant relative orientations with their neighbors.Finally,numeric simulations are provided to demonstrate the effectiveness of the proposed control algorithms.

关键词： Multi-agent systems Formation spacecraft Attitude control coordinated tracking

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Neural Network Based Adaptive tracking of Nonlinear Multi-Agent System

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Journal of Electronic Science and Technology 2021年第2期19卷 144-154页

作者： Bo-Xian Lin Wei-Hao Li Kai-Yu Qin Xi Chen School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaChengdu 611731

In this paper,the problems of robust consensus tracking control for the second-order multi-agent system with uncertain model parameters and nonlinear disturbances are considered.An adaptive control strategy is proposed to smooth the agent’s trajectory,and the neural network is constructed to estimate the system’s unknown components.The consensus conditions are demonstrated for tracking a leader with nonlinear dynamics under an adaptive control algorithm in the absence of model uncertainties.Then,the results are extended to the system with unknown time-varying disturbances by applying the neural network estimation to compensating for the uncertain parts of the agents’models.Update laws are designed based on the Lyapunov function terms to ensure the effectiveness of robust control.Finally,the theoretical results are verified by numerical simulations,and a comparative experiment is conducted,showing that the trajectories generated by the proposed method exhibit less oscillation and converge faster.

关键词： coordinated tracking leader following consensus neural network based adaptive control robust control uncertain nonlinear system

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