线性抛物型偏微分方程描述系统的时间次优反馈控制

IF 2 4区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Optimal Control Applications & Methods Pub Date : 2007-10-29 DOI:10.1002/OCA.4660030206
Kin Tuck Wong, R. Luus
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引用次数: 0

摘要

从次优的角度考虑了线性抛物型偏微分方程系统的反馈控制问题。首先用一个标量二次函数表示与期望分布的偏差,然后通过在每个时间步上最小化这个二次函数来最大化接近目标的速率。利用正交配置技术可以建立精确的低阶集总参数模型。直接搜索优化可以得到最优的二次函数,然后得到最优的反馈增益矩阵。由此产生的控制作用于扩散过程,使系统快速而稳定地到达目标。
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Time suboptimal feedback control of systems described by linear parabolic partial differential equations
Feedback control for systems described by linear parabolic partial differential equations is considered from a time suboptimal point of view. A scalar quadratic function representing the deviation from a desired distribution is first formulated, and the rate of approach to the target is maximized by minimizing this quadratic function at each time step. An orthogonal collocation technique enables an accurate low-order lumped parameter model to be constructed. A direct search optimization can then be used to obtain the optimal quadratic function and, subsequently, the optimal feedback gain matrix for control. The resulting control applied to a diffusion process takes the system to the target rapidly and in a stable manner.
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来源期刊
Optimal Control Applications & Methods
Optimal Control Applications & Methods 工程技术-应用数学
CiteScore
3.90
自引率
11.10%
发文量
108
审稿时长
3 months
期刊介绍: Optimal Control Applications & Methods provides a forum for papers on the full range of optimal and optimization based control theory and related control design methods. The aim is to encourage new developments in control theory and design methodologies that will lead to real advances in control applications. Papers are also encouraged on the development, comparison and testing of computational algorithms for solving optimal control and optimization problems. The scope also includes papers on optimal estimation and filtering methods which have control related applications. Finally, it will provide a focus for interesting optimal control design studies and report real applications experience covering problems in implementation and robustness.
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