Y. Guo and G. Chen, “Robust Near-Optimal Coordination in Uncertain Multiagent Networks With Motion Constraints,” in IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2021.3125318.

文章目录

  • 1. Introduction
  • 2. Problem formulation
    • 2.1 Algebraic graph theory
    • 2.2 System description
    • 2.3 Optimal coordination control problem formulation
  • 3. Main results
    • 3.1 Dynamic programming-based optimization solution
    • 3.2 Robust control law design in ADP framework
    • 3.3 Closed-loop stability and performance analysis
      • 定理 1
  • 4. Numerical simulations
    • 4.1 Six agents maneuvering through two obstacles

1. Introduction

2. Problem formulation

2.1 Algebraic graph theory

2.2 System description

2.3 Optimal coordination control problem formulation

本节将上述运动受限的协调控制目标描述为一个最佳协调问题。

3. Main results

本节基于ADP框架和稳定性分析,推导出鲁棒的接近最优的多Agent协调控制器设计。

3.1 Dynamic programming-based optimization solution

在动态编程解决方案中,问题变成了找出局部最优价值函数 Vi∗(δi)V_i^*(\delta_i)Vi∗​(δi​),当存在复杂的运动约束时,这通常不可能得到分析解决方案。为了克服这一困难,我们将开发一种新的近似动态编程算法来近似最优值函数。

3.2 Robust control law design in ADP framework

本节介绍了一种鲁棒且分布式的基于单层神经网络的ADP技术,验证近似最优解决方案。

3.3 Closed-loop stability and performance analysis

定理 1

假设假设1-5得到满足。考虑非线性二阶多代理系统(1),其控制算法由(22)-(26)给出。那么,权重估计误差 W~i\tilde{W}_iW~i​ 和矢量 δi\delta_iδi​ 为UUB,多Agent系统的防撞和速度约束一直得到保证。此外,协调控制输入接近于最优控制输入 ui∗(t)u_i^∗(t)ui∗​(t),即 sup⁡∥u^i(t)−ui∗(t)∥≤εui\sup \|\hat{u}_i(t)-u_i^∗(t)\| \le \varepsilon_{u_i}sup∥u^i​(t)−ui∗​(t)∥≤εui​​,εui\varepsilon_{u_i}εui​​ 为正常数。

4. Numerical simulations

本节通过数值模拟验证了定理 1 的有效性。

4.1 Six agents maneuvering through two obstacles

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