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Predictor-like feedback for actuator and sensor dynamics governed by diffusion PDEs

机译:由扩散PDE控制的执行器和传感器动力学的类似预测器的反馈

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For (possibly unstable) ODE systems with actuator delay, predictor-based infinite-dimensional feedback can compensate for actuator delay of arbitrary length and achieve stabilization. We extend this concept to another class of PDE-ODE cascades, where the infinite-dimensional part of the plant is of diffusive, rather than convective type. We derive predictor-like feedback laws and observers, with explicit gain kernels. The gain kernels involve second order matrix exponentials of the system matrix of the ODE plant, which is the result of the second-order-in-space character of the actuator/sensor dynamics. The construction of the kernel functions is performed using the continuum version of the backstepping method. Robustness to small perturbations in the diffusion coefficient is proved.
机译:对于具有执行器延迟的(可能是不稳定的)ODE系统,基于预测变量的无限维反馈可以补偿任意长度的执行器延迟并实现稳定。我们将此概念扩展到另一类PDE-ODE级联,其中植物的无限维部分是扩散型而不是对流型。我们导出具有明确增益内核的类似于预测变量的反馈定律和观察者。增益内核涉及ODE设备的系统矩阵的二阶矩阵指数,这是执行器/传感器动力学的二阶空间特征的结果。使用backstepping方法的连续版本执行内核功能的构建。证明了扩散系数小的扰动的鲁棒性。

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