对于具有非线性故障的多代理系统,事件触发的自适应预分配的有限时间共识控制.
IEEE transactions on cybernetics
|September 12, 2024
概括
本研究介绍了非线性多元代理系统的新控制策略,提高了性能和资源效率. 基于神经适应障碍利亚普诺夫函数 (BLF) 的方法确保有限时间共识和非对称跟踪,即使存在不确定性和故障.
科学领域:
- 控制理论 控制理论
- 人工智能的人工智能
- 系统工程 系统工程
背景情况:
- 非线性多代理系统 (MAS) 由于高阶动态,不确定性和外部干扰而存在重大控制挑战.
- 现有的控制方法经常与通信网络中的非细非线性故障和资源限制作斗争.
研究的目的:
- 开发一种基于莱普诺夫函数 (BLF) 的神经适应障碍事件触发控制,用于在非线性MAS中预先分配的有限时间共识和非对称跟踪.
- 为了解决动态不确定性,外部干扰,在代理的动态中的非affine非线性故障.
- 通过一种新的动态事件触发机制来提高通信效率.
主要方法:
- 利用神经网络 (NN) 来近似未知的非线性动力学和巴特沃思低通波器来处理非非因断.
- 引入了一个动态事件触发机制,增强了切换值,以节省通信资源.
- 定义了一个预分配的有限时间性能函数 (PFTPF),以优化瞬态和稳定状态性能.
- 采用基于BLF的自适应控制器,具有平滑的功能和信号局限性和错误收的下降变量.
主要成果:
- 拟议的控制策略确保所有信号仍然受到限制.
- 同步错误实际上仅限于定义的PFTPF.
- 追踪错误异常地汇聚到零,证明了有效的控制.
- 该方法成功地处理动态不确定性,外部干扰和非精细非线性断层.
结论:
- 基于神经适应BLF的新型事件触发控制方法对于非线性MAS是可行的和有效的.
- 该方法实现了预先分配的有限时间共识和非对称跟踪,提高了性能和资源效率.
- 拟议的框架为复杂的多代理系统控制问题提供了可靠的解决方案.
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