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Development of robust intelligent tracking control system for uncertain nonlinear systems using H~∞ control technique

机译:基于H〜∞控制技术的不确定非线性系统鲁棒智能跟踪控制系统的开发

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摘要

In this paper, a robust intelligent tracking control (RITC) system employs an adaptive output recurrent cerebellar model articulation controller (ORCMAC) is developed for uncertain nonlinear system to achieve H~∞ tracking performance. The proposed dynamic structure of ORCMAC has superior capability in efficient learning mechanism and dynamic response. Temporal relations are embedded in conventional cerebellar model articulation controller (CMAC) by adding feedback connections between the output space and input space, so that the ORCMAC captures the system dynamic. In the RITC design, the Taylor linearization technique is employed to increase the learning ability of ORCMAC and the on-line adaptive laws are derived based on the Lyapunov stability analysis, the sliding mode control methodology and the H~∞ control technique so that the stability of the closed-loop system and H~∞ tracking performance can be guaranteed. Finally, the proposed control system is applied to control an inverted pendulum system, a Van der Pol oscillator and a Genesio chaotic system. Simulation results demonstrate that the proposed control scheme can achieve favorable tracking performances for the uncertain nonlinear systems with unknown dynamic functions and under the occurrence of external disturbance.
机译:本文针对不确定的非线性系统,开发了一种采用自适应输出递归小脑模型关节控制器(ORCMAC)的鲁棒智能跟踪控制(RITC)系统,以实现H〜∞跟踪性能。提出的ORCMAC的动态结构在高效的学习机制和动态响应方面具有卓越的能力。通过在输出空间和输入空间之间添加反馈连接,将时间关系嵌入到常规的小脑模型关节控制控制器(CMAC)中,以便ORCMAC捕获系统动态。在RITC设计中,采用泰勒线性化技术来提高ORCMAC的学习能力,并基于Lyapunov稳定性分析,滑模控制方法和H〜∞控制技术推导了在线自适应律。可以保证闭环系统的跟踪性能和H〜∞跟踪性能。最后,将所提出的控制系统应用于控制倒立摆系统,范德波尔振荡器和Genesio混沌系统。仿真结果表明,所提出的控制方案对于动态函数未知且存在外部扰动的不确定非线性系统具有良好的跟踪性能。

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