Suboptimal sensors location in the state estimation problem for stochastic non-linear distributed parameter systems

This work proposes a state estimation strategy over mobile sensor–actuator networks with missing measurements for a class of distributed parameter systems (DPSs) with time-varying delay. Initially, taking advantage of the abstract development equation theory and operator semigroup method, this kind of delayed DPSs described by partial differential equations (PDEs) is derived for evolution equations. Subsequently, the distributed state estimators including consistency component and gain component are designed; the purpose is to estimate the original state distribution of the delayed DPSs with missing measurements. Then, a delay-dependent guidance approach is presented in the form of mobile control forces by constructing an appropriate Lyapunov function candidate. Furthermore, by applying Lyapunov stability theorem, operator semigroup theory, and a stochastic analysis approach, the estimation error systems have been proved asymptotically stable in the mean square sense, which indicates the estimators can approximate the original system states effectively when this kind of DPS has time-delay and the mobile sensors occur missing measurements. Finally, the correctness of control strategy is illustrated by numerical simulation results.

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On SISO and MIMO variable structure control of non linear distributed parameter systems: application to fixed bed reactors

Journal of Process Control ◽

10.1016/s0959-1524(03)00004-0 ◽

2003 ◽

Vol 13 (8) ◽

pp. 729-737 ◽

Cited By ~ 13

Author(s):

Olfa Boubaker ◽

Jean-Pierre Babary

Keyword(s):

Fixed Bed ◽

Variable Structure Control ◽

Variable Structure ◽

Distributed Parameter Systems ◽

Distributed Parameter ◽

Structure Control ◽

Fixed Bed Reactors ◽

Non Linear

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Set-membership filtering for automatic guided vehicles with unknown-but-bounded noises

Transactions of the Institute of Measurement and Control ◽

10.1177/01423312211043666 ◽

2021 ◽

pp. 014233122110436

Author(s):

Hao Yang ◽

Yilian Zhang ◽

Wei Gu ◽

Fuwen Yang ◽

Zhiquan Liu

Keyword(s):

State Estimation ◽

Estimation Algorithm ◽

The State ◽

Estimation Problem ◽

Filtering Method ◽

Automatic Guided Vehicles ◽

Tracking Process ◽

Set Membership ◽

Text Filtering ◽

System States

This paper is concerned with the state estimation problem for an automatic guided vehicle (AGV). A novel set-membership filtering (SMF) scheme is presented to solve the state estimation problem in the trajectory tracking process of the AGV under the unknown-but-bounded (UBB) process and measurement noises. Different from some existing traditional filtering methods, such as Kalman filtering method and [Formula: see text] filtering method, the proposed SMF scheme is developed to provide state estimation sets rather than state estimation points for the system states to effectively deal with UBB noises and reduce the requirement of the sensor precision. Then, in order to obtain the state estimation ellipsoids containing the true states, a set-membership estimation algorithm is designed based on the AGV physical model and S-procedure technique. Finally, comparison examples are presented to illustrate the effectiveness of the proposed SMF scheme for an AGV state estimation problem in the present of the UBB noises.

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