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A Low-Complexity Control Method with Guaranteed Performance for Nonlinear Large-Scale Non-Triangular Structure Systems

机译:一种低复杂性控制方法,具有保证性能的非线性大规模非三角形结构系统

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This work focuses on low-complexity prescribed performance control (PPC) for nonlinear large-scale non-triangular- structured dynamics whose system nonlinearities and control gain functions are relaxed to rely on the whole state vector. The peculiarity of this extended class is that the restrictive assumption that the unknown nonlinear functions must satisfy Lipschitz or setting bounding function conditions is removed and only the continuity of nonlinearities is required. A novel low-complexity prescribed performance control method is skillfully incorporated into backstepping technique so as to guarantee closed-loop stability while some transient and steady state performances can be also achieved. Different from the state of the art has focused on the PPC method, neither approximators (neural networks and fuzzy logic systems) nor adaptation technique are employed in the control design which alleviate the computation burden.
机译:这项工作侧重于非线性大规模非三角结构动态的低复杂性规定的性能控制(PPC),其系统非线性和控制增益函数被放宽以依赖于整个状态向量。该扩展课程的特殊性是,未知非线性函数必须满足LipsChitz或设置限定功能条件的限制假设,并且仅需要非线性的连续性。一种新的低复杂性规定的性能控制方法巧妙地结合到BackStepping技术中,以便能够保证闭环稳定性,而可以实现一些瞬态和稳态的性能。与本领域的状态不同,专注于PPC方法,既不是近似器(神经网络和模糊逻辑系统)也不采用适应技术,控制设计缓解计算负担。

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