Improving control and estimation for distributed parameter systems utilizing mobile actuator–sensor network

Mu, Wenying; Cui, Baotong; Li, Wen; Jiang, Zhengxian

doi:10.1016/j.isatra.2014.05.004

Cited by 22 publications

(13 citation statements)

References 17 publications

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“…Note that, here, we are neglecting the dynamics of the mobile sensor compared to the dynamics of Σ 1 . This reasoning can be extended to a network of mobile sensors as in [29,30,31].…”

Section: Intermittent Sensingmentioning

confidence: 99%

See 2 more Smart Citations

Boundary Control of the Kuramoto-Sivashinsky Equation Under Intermittent Data Availability: With Proofs

Maghenem¹,

Prieur²,

Witrant³

2022

Preprint

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In this paper, two boundary controllers are proposed to stabilize the origin of the nonlinear Kuramoto-Sivashinsky equation under intermittent measurements. More precisely, the spatial domain is divided into two subdomains. The state of the system on the first sub-domain is measured along a given interval of time, and the state on the remaining sub-domain is measured along another interval of time. Under the proposed sensing scenario, we control the considered equation by designing the value of the state at three isolated spatial points, the two extremities of the spatial domain plus one inside point. Furthermore, we impose a null value for the spatial gradient of the state at these three locations. Under such a control loop, we propose two types of controllers and we analyze the stability of the resulting closed-loop system in each case. The paper is concluded with some discussions and future works.

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“…Note that, here, we are neglecting the dynamics of the mobile sensor compared to the dynamics of Σ 1 . This reasoning can be extended to a network of mobile sensors as in [29,30,31].…”

Section: Intermittent Sensingmentioning

confidence: 99%

“…and γ are related via (29). Next, we introduce the scalar (infinite-dimensional) differential inequality…”

Section: Proof Of Theoremmentioning

confidence: 99%

See 1 more Smart Citation

Boundary Control of the Kuramoto-Sivashinsky Equation Under Intermittent Data Availability: With Proofs

Maghenem¹,

Prieur²,

Witrant³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…The team of Demetriou acquired fruitful results about the estimation problem over mobile sensor networks or mobile agents networks [37][38][39][40]; then, Demetriou and Egorova ulteriorly estimated the release of gases into the atmosphere using drones and calculating fluid dynamics [41]. Mu et al [42] improved and enhanced the estimation performance and convergence speed. Furthermore, Jiang and Cui [43] studied the estimation problem about missing measurements in the fixed sensor networks, then they extended the research to mobile sensor networks [44].…”

Section: Introductionmentioning

confidence: 99%

State Estimation for a Class of Distributed Parameter Systems with Time-Varying Delay over Mobile Sensor–Actuator Networks with Missing Measurements

Cui

Zhuang

et al. 2021

Mathematics

Self Cite

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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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“…By utilizing the distributed in space measurements, a network-based H ∞ filter for parabolic PDEs systems with the objective of enlarging the sampling time intervals to reduce the amount of communications while preserving a prescribed error system performance was designed in [32]. Other more recent researches can be referred in [33,34].…”

Section: Introductionmentioning

confidence: 99%

Quantized State Feedback-Based H∞ Control for Nonlinear Parabolic PDE Systems via Finite-Time Interval

Chang¹,

Li²,

Park³

2021

Preprint

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In this paper, the finite-time H∞ control problem of nonlinear parabolic partial differential equation (PDE) systems with parametric uncertainties is studied. Firstly, based on the definition of the quantiser, static state feedback controller and dynamic state feedback controller with quantization are presented, respectively. The finite-time H∞ control design strategies are subsequently proposed to analyze the nonlinear parabolic PDE systems with respect to the effect of quantization. And by constructing appropriate Lyapunov functionals for the studied systems, sufficient conditions for the existence of the feedback control gains and the quantizer’s adjusting parameters which guarantee the prescribed attenuation level of H∞ performance are expressed as nonlinear matrix inequalities. Then, by using some inequalities and decomposition technic, the nonlinear matrix inequalities are transformed to standard linear matrix inequalities (LMIs). Moreover, the optimal H∞ control performances are pursued by solving optimization problems subject to the LMIs. Finally, to illustrate the feasibility and effectiveness of the finite-time H∞ control design strategies, an application to the catalytic rod in a reactor is explored.

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Improving control and estimation for distributed parameter systems utilizing mobile actuator–sensor network

Cited by 22 publications

References 17 publications

Boundary Control of the Kuramoto-Sivashinsky Equation Under Intermittent Data Availability: With Proofs

Boundary Control of the Kuramoto-Sivashinsky Equation Under Intermittent Data Availability: With Proofs

State Estimation for a Class of Distributed Parameter Systems with Time-Varying Delay over Mobile Sensor–Actuator Networks with Missing Measurements

Quantized State Feedback-Based H∞ Control for Nonlinear Parabolic PDE Systems via Finite-Time Interval

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