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Adaptive non-backstepping fuzzy tracking control for a class of multiple-input–multiple-output pure-feedback systems with unknown dead-zones

机译:一类未知死区的多输入多输出纯反馈系统的自适应无反步模糊跟踪控制

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摘要

In this study, the authors present a novel adaptive non-back-stepping alleviating computation tracking control algorithm for a class of MIMO pure-feedback systems with unknown dead-zone inputs. Based on the introduced new state variables and coordinate transforms, the pure-feedback form is converted into a normal form where back-stepping scheme is not necessary. Owing to the unavailability of the new states, the tracking control problem is changed from a state-feedback one to an output-feedback one. Therefore, observers need to be designed to estimate the indirect un-measurable states. In the controller and observer design procedure, the control method is based on non-back-stepping scheme and for each subsystem only three adaptive adjusted parameters are needed to be updated on-line. Thus, different from the back-stepping-based ones, this new algorithm can not only alleviate on-line computation burden but also can considerably simplify the control procedure. According to Lyapunov stable analysis methods, the bounded of all the signals in the closed-loop system can be guaranteed and the tracking error is proven to converge to a small neighbourhood of the origin. Simulation results are presented to illustrate the effectiveness of this proposed approach.
机译:在这项研究中,作者提出了一种新颖的自适应无反步缓和计算跟踪控制算法,用于一类具有未知死区输入的MIMO纯反馈系统。基于引入的新状态变量和坐标变换,将纯反馈形式转换为不需要反步法的常规形式。由于新状态的不可用,跟踪控制问题从状态反馈状态变为输出反馈状态。因此,需要设计观察者来估计间接的不可测量状态。在控制器和观察者的设计过程中,控制方法基于非后退方案,并且对于每个子系统,仅需要三个自适应调整后的参数即可进行在线更新。因此,与基于反步的算法不同,该新算法不仅可以减轻在线计算的负担,而且可以大大简化控制过程。根据Lyapunov稳定分析方法,可以保证闭环系统中所有信号的有界,并且跟踪误差已证明收敛到原点的一个小邻域。仿真结果表明了该方法的有效性。

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