初始状态不确定的非线性过程系统状态估计的鲁棒粒子滤波方法

doi:10.11949/j.issn.0438-1157.20151440

化工学报 ›› 2016, Vol. 67 ›› Issue (9): 3826-3832.DOI: 10.11949/j.issn.0438-1157.20151440

初始状态不确定的非线性过程系统状态估计的鲁棒粒子滤波方法

曹婷婷, 张正江, 郑崇伟

温州大学物理与电子信息工程学院, 浙江温州 325035

收稿日期:2015-09-11 修回日期:2016-05-04 出版日期:2016-09-05 发布日期:2016-09-05
通讯作者: 张正江
基金资助:
国家自然科学基金项目（61374167）；浙江省自然科学基金项目（LQ14F030006）；浙江省科技计划项目（2015C31157，2014C31074，2014C31093）。

A robust particle filter for estimating states in nonlinear process systems with uncertain initial states

CAO Tingting, ZHANG Zhengjiang, ZHENG Chongwei

College of Physics and Electronic Information Engineering, Wenzhou University, Wenzhou 325035, Zhejiang, China

Received:2015-09-11 Revised:2016-05-04 Online:2016-09-05 Published:2016-09-05
Supported by:
supported by the National Natural Science Foundation of China (61374167), the Natural Science Foundation of Zhejiang Province (LQ14F030006) and the Science and Technology Planning Project of Zhejiang Province (2015C31157, 2014C31074, 2014C31093).

摘要/Abstract

摘要：

在过程系统的控制与故障检测等方面，状态估计发挥着重要作用。针对非线性过程系统状态估计过程中初始状态不确定性问题，提出一种鲁棒粒子滤波方法。该方法首先引入初始状态准确性间接判定准则，根据判定的结果来选择是否进行基于观测偏差反馈机制的初始状态迭代改进。初始值准确性较差时，可以通过初始状态迭代改进策略使最终的初始粒子更接近真实的初始状态，从而增加产生初始粒子的正确性概率，通过粒子滤波迭代得到更准确的状态估计结果。将提出的鲁棒粒子滤波方法与传统粒子滤波方法应用于两个非线性动态系统实例中，结果验证了所提出方法的有效性与鲁棒性。

关键词: 非线性过程系统, 初始状态, 状态估计, 鲁棒粒子滤波方法

Abstract:

State estimation is critical for both process control and fault detection. A robust particle filter was proposed to estimate states in nonlinear process systems with uncertainty of initial states, which an indirect acceptance criterion was introduced to determine accuracy of the initial states and then to decide the needs for iterative improvement on the initial states by the feedback mechanism of observation bias. In case that the initial states were inaccurate, the iterative improvement strategy would be triggered to adjust particles closer to the true initial states. Therefore, the probability of setting the correct initial states to particles was increased and the accuracy of state estimation was improved through particle filter iteration. When applied to two nonlinear dynamic systems, the proposed particle filter demonstrated much more effectiveness and robustness than the traditional particle filter.

Key words: nonlinear process system, initial states, state estimation, robust particle filter

中图分类号:

TQ021.8

曹婷婷, 张正江, 郑崇伟. 初始状态不确定的非线性过程系统状态估计的鲁棒粒子滤波方法[J]. 化工学报, 2016, 67(9): 3826-3832.

CAO Tingting, ZHANG Zhengjiang, ZHENG Chongwei. A robust particle filter for estimating states in nonlinear process systems with uncertain initial states[J]. CIESC Journal, 2016, 67(9): 3826-3832.

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初始状态不确定的非线性过程系统状态估计的鲁棒粒子滤波方法

A robust particle filter for estimating states in nonlinear process systems with uncertain initial states

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