具有混合执行器故障和多未知控制方向的多智能体编队系统自适应协同容错控制

针对非线性多智能体具有混合执行器故障和多未知控制方向的问题，基于鲁棒自适应模糊技术，提出新颖的协同容错控制方法。采用分段Nussbaum函数解决了多未知控制方向；基于鲁棒自适应模糊技术解决了系统中的非线性不确定问题；引入一阶滑模微分器与自适应反步技术结合，用于获得虚拟控制律的一阶导数，并结合鲁棒有界方法，用于提高所设计的自适应协同控制器的收敛速度和追踪精度；基于代数图论，建立了智能体系统的误差模型，设计了分布式一致协同容错控制器，构建了李雅普诺夫候选函数，证明了所设计的控制器能够使得系统稳定。通过对比仿真实例，验证了所提方法的有效性，为工程实践提供了理论支撑。

Adaptive collaborative fault tolerance for multi-agent formation system with hybrid actuator faults and multiple unknown control directions

The cooperative fault-tolerant for the nonlinear multi-agent system with hybrid actuator faults and multiple unknown control directions were investigated, based on the RAFSMT(robust adaptive fuzzy sliding mode technology). The piecewise Nussbaum function was used to solve the multiple unknown control directions, and the robust adaptive fuzzy technology was used to solve the nonlinear uncertainty in the system. A first-order sliding mode differentiator was introduced, and it was combined with the adaptive backstepping technique to obtain the first-order derivative of the virtual control law. At the same time, a robust bounded method was adopted to improve the convergence speed and tracking accuracy of the designed adaptive cooperative controller. Based on the algebraic graph theory, the error model of the agent system was established, the distributed consensus cooperative fault-tolerant controller was designed, and the Lyapunov candidate function was constructed to prove that the proposed controller can make the system stable. The effectiveness of the proposed method is verified by the comparison of simulation examples, which provides theoretical support for engineering practice.