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Hybrid Fuzzy Adaptive Output Feedback Control Design for Uncertain MIMO Nonlinear Systems With Time-Varying Delays and Input Saturation

机译:时滞和输入饱和的不确定MIMO非线性系统的混合模糊自适应输出反馈控制设计

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摘要

In this paper, a hybrid fuzzy adaptive output feedback control design approach is proposed for a class of multiinput and multioutput strict-feedback nonlinear systems with unknown time-varying delays, unmeasured states, and input saturation. First, fuzzy logic systems are employed to approximate unknown nonlinear functions in the system. Next, a smooth function is used to approximate the input saturation and an adaptive fuzzy state observer is constructed to solve the problem of unmeasured states. Based on the designed adaptive fuzzy state observer, a serial-parallel estimation model is established. By applying adaptive fuzzy dynamic surface control technique and utilizing the prediction error between the system states observer model and the serial–parallel estimation model, a new fuzzy controller with the composite parameters adaptive laws is developed based on Lyapunov–Krasovskii functional. It is proved that all variables of the closed-loop system are bounded and the system outputs can follow the given bounded reference signals as close as possible. A simulation example is provided to further show the effectiveness of this novel control scheme.
机译:针对一类具有未知时变时滞,未测状态和输入饱和的多输入多输出严格反馈非线性系统,提出了一种混合模糊自适应输出反馈控制设计方法。首先,采用模糊逻辑系统来近似系统中未知的非线性函数。接下来,使用平滑函数近似输入饱和度,并构建自适应模糊状态观察器以解决未测状态的问题。基于设计的自适应模糊状态观测器,建立了串并行估计模型。通过应用自适应模糊动态表面控制技术并利用系统状态观测器模型与串行-并行估计模型之间的预测误差,基于Lyapunov–Krasovskii函数,开发了一种具有复合参数自适应律的新型模糊控制器。事实证明,闭环系统的所有变量都是有界的,并且系统输出可以尽可能接近给定的有界参考信号。提供了一个仿真示例,以进一步显示该新颖控制方案的有效性。

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