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Distributed proportional plus second-order spatial derivative control for distributed parameter systems subject to spatiotemporal uncertainties

机译:时空不确定性的分布式参数系统的分布式比例加二阶空间导数控制

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摘要

In this paper, a robust distributed control design based on proportional plus second-order spatial derivative (P-sD2) is proposed for exponential stabilization and minimization of spatial variation of a class of distributed parameter systems (DPSs)with spatiotemporal uncertainties, whose model is represented by parabolic partial differential equations with spatially varying coefficients. Based on the Lyapunov's direct method, a robust distributed P-sD2 controller is developed to not only exponentially stabilize the DPS for all admissible spatiotemporal uncertainties but also minimize the spatial variation of the process. The outcome of the robust distributed P-sD2 control problem is formulated as a spatial differential bilinear matrix inequality (SDBMI) problem. A local optimization algorithm that the SDBMI is treated as a double spatial differential linear matrix inequality (SDLMI) is presented to solve this SDBMI problem. Furthermore, the SDLMI optimization problem can be approximately solved via the finite difference method and the existing convex optimization techniques. Finally, the proposed design method is successfully applied to feedback control problem of the FitzHugh-Nagumo equation.
机译:本文提出了一种基于比例加二阶空间导数(P-sD2)的鲁棒分布式控制设计,用于一类具有时空不确定性的分布参数系统(DPS)的指数稳定和空间变异最小化,其模型为由具有空间变化系数的抛物型偏微分方程表示。基于Lyapunov的直接方法,开发了一种鲁棒的分布式P-sD2控制器,该控制器不仅可以针对所有可接受的时空不确定性以指数形式稳定DPS,而且还可以使过程的空间变化最小化。鲁棒的分布式P-sD2控制问题的结果被表述为空间差分双线性矩阵不等式(SDBMI)问题。提出了一种将SDBMI视为双重空间微分线性矩阵不等式(SDLMI)的局部优化算法,以解决该SDBMI问题。此外,可以通过有限差分法和现有的凸优化技术来近似解决SDLMI优化问题。最后,将所提出的设计方法成功应用于FitzHugh-Nagumo方程的反馈控制问题。

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