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A Dynamic Decoupling Approach to Robust T–S Fuzzy Model-Based Control

机译:基于鲁棒TS模糊模型控制的动态解耦方法

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In this paper, a dynamic decoupling approach is proposed to improve the robust Takagi–Sugeno (T–S) fuzzy model-based control to cope with system uncertainty, input actuator nonlinearity, and input time delay. First, the basic dynamic decoupling concept is introduced by involving virtual input dynamics, such that the system uncertainty and control input are decoupled in each fuzzy rule. This leads to simplified linear matrix inequality (LMI) conditions. Next, the dynamic decoupling approach is extended to controlling uncertain systems with input actuator nonlinearity (e.g., saturation, quantization, dead-zone, etc.) or time-varying input delay. Due to the decoupling between uncertainty, actuator nonlinearity, and input delay, more relaxed stability conditions are obtained for the asymptotic stability and $H^{infty }$ control performance. Furthermore, the limit on the initial condition is removed when considering input saturation. Larger and faster time-varying state and input delays are allowed under fewer LMIs. Finally, to show the advantages of the developed control method, numerical simulations are carried out on an inverted pendulum (subject to either the saturation, quantization, or delay input), a delay mass–spring–damper system, and a delay truck–trailer system.
机译:在本文中,提出了一种动态去耦方法来改善鲁棒的Takagi-Sugeno(TS)基于模糊模型的控制,以应对系统不确定性,输入执行器非线性和输入时间延迟的问题。首先,通过涉及虚拟输入动力学来引入基本的动态解耦概念,以使系统不确定性和控制输入在每个模糊规则中均被解耦。这导致简化的线性矩阵不等式(LMI)条件。接下来,将动态去耦方法扩展到控制具有输入致动器非线性(例如,饱和度,量化,死区等)或时变输入延迟的不确定系统。由于不确定性,执行器非线性和输入延迟之间的解耦,渐近稳定性和 $ H ^ {infty} $ 可获得更宽松的稳定性条件。 tex> 控制性能。此外,当考虑输入饱和时,将取消初始条件的限制。更少的LMI允许更大和更快的时变状态和输入延迟。最后,为了显示开发的控制方法的优势,在倒立摆(受饱和,量化或延迟输入的影响),延迟质量弹簧-阻尼器系统和延迟卡车-拖车上进行了数值模拟。系统。

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