Cungen Liu , Yulong Sun , Xiaoping Liu , Na Liu , Huanqing Wang
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引用次数: 0
Abstract
This paper is devoted to the design of adaptive nonlinear prescribed performance controllers for balancing constraint and robustness. Firstly, a shift function is introduced to enhance robustness in the initial stage. Secondly, a new finite-time performance function and a regulation of dynamic adjustments are developed for the first time. Due to the regulation, it can be prevented by the proposed scheme that tracking errors approach or exceed performance boundaries during operation, which ensures both robustness and constraint, and the performance function is differentiable of order n, which can be used in backstepping design for higher-order systems without approximators. Finally, the designed controller is more robust in both transient and stable states, whose effectiveness and superiority are validated by stability analysis, matlab simulation, and an actual test on a real robotic arm.
本文致力于设计兼顾约束性和鲁棒性的自适应非线性规定性能控制器。首先，在初始阶段引入了移位函数来增强鲁棒性。其次，首次开发了一种新的有限时间性能函数和动态调整调节器。由于有了调节，所提出的方案可以防止运行过程中跟踪误差接近或超过性能边界，从而确保了鲁棒性和约束性，而且性能函数是 n 阶可微的，可用于无近似值的高阶系统的反步进设计。最后，所设计的控制器在瞬态和稳定状态下都具有更强的鲁棒性，其有效性和优越性通过稳定性分析、matlab 仿真和在真实机械臂上的实际测试得到了验证。
期刊介绍：
The European Control Association (EUCA) has among its objectives to promote the development of the discipline. Apart from the European Control Conferences, the European Journal of Control is the Association''s main channel for the dissemination of important contributions in the field.
The aim of the Journal is to publish high quality papers on the theory and practice of control and systems engineering.
The scope of the Journal will be wide and cover all aspects of the discipline including methodologies, techniques and applications.
Research in control and systems engineering is necessary to develop new concepts and tools which enhance our understanding and improve our ability to design and implement high performance control systems. Submitted papers should stress the practical motivations and relevance of their results.
The design and implementation of a successful control system requires the use of a range of techniques:
Modelling
Robustness Analysis
Identification
Optimization
Control Law Design
Numerical analysis
Fault Detection, and so on.
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