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Robust tracking designs for both holonomic and nonholonomic constrained mechanical systems: adaptive fuzzy approach

机译:完整和非完整约束机械系统的鲁棒跟踪设计:自适应模糊方法

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摘要

Adaptive fuzzy-based tracking control designs are proposed in the paper for both holonomic mechanical systems as well as a large class of nonholonomic mechanical systems with plant uncertainties and external disturbances. A unified and systematic procedure is employed to derive the controllers for both holonomic and nonholonomic mechanical control systems, respectively. First, a fuzzy logic system is introduced to learn the behavior of unknown (or uncertain) mechanical dynamics by using an adaptive algorithm. Next, the effect of approximation error on the tracking error must be efficiently eliminated by employing an additional robustifying algorithm. Consequently, hybrid adaptive-robust controllers can be constructed such that the resulting closed-loop mechanical systems guarantee a satisfactorily transient and asymptotic performance. Furthermore, a partitioned procedure with respect to the above developed adaptive fuzzy logic approximators is introduced such that the number of fuzzy IF-THEN rules is significantly reduced and the developed control schemes can be easily implemented from the viewpoint of practical applications. Finally, simulation examples are presented to illustrate the tracking performance of a two-link constrained robot manipulator and a vertical wheel rolling on a plane surface by the proposed adaptive fuzzy-based control algorithms.
机译:本文针对完整的机械系统以及一类具有工厂不确定性和外部干扰的非完整机械系统,提出了基于自适应模糊的跟踪控制设计。采用统一和系统的程序分别导出完整和非完整机械控制系统的控制器。首先,引入模糊逻辑系统,以通过使用自适应算法来学习未知(或不确定)机械动力学的行为。接下来,必须通过采用其他鲁棒化算法来有效消除近似误差对跟踪误差的影响。因此,可以构造混合自适应鲁棒控制器,以使所得的闭环机械系统确保令人满意的瞬态和渐近性能。此外,针对上述开发的自适应模糊逻辑逼近器引入了分区过程,从而从实际应用的角度来看,大大减少了模糊IF-THEN规则的数量,并且可以轻松地实现所开发的控制方案。最后,通过仿真实例说明了基于自适应模糊控制算法的双链约束机器人操纵器和垂直轮在平面上滚动的跟踪性能。

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