Interval State Estimator Design for Linear Parameter Varying (LPV) Systems

Khan, Awais Gul; Bai, Xiaoshan; Zhang, Bo; Yan, Peiguang

doi:10.1109/tcsii.2021.3057107

Cited by 12 publications

(4 citation statements)

References 21 publications

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“…Li [3] studies UIO design for LPV systems in the presence of bounded error by integrating the decoupling technique and set-membership method. As a special form of UIO, interval observer (IO) designs for LPV systems can be found in [7][8][9][10][11][12]. Khan [11] proposes a new design method of interval state estimator for an LPV system subject to state disturbances and measurement noises using the observability matrix.…”

Section: Introductionmentioning

confidence: 99%

“…As a special form of UIO, interval observer (IO) designs for LPV systems can be found in [7][8][9][10][11][12]. Khan [11] proposes a new design method of interval state estimator for an LPV system subject to state disturbances and measurement noises using the observability matrix. In [12], the finite-time control design for an LPV system is studied via the interval method, where an interval observer is constructed using an unknown input observer to avoid co-constraints in the estimation error dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Consensus Control of Linear Parameter-Varying Multi-Agent Systems with Unknown Inputs

Zhu

Tan

2023

Sensors

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This paper investigates the observer-based consensus control problem for linear parameter-varying (LPV) multi-agent systems (MASs) with unknown inputs. Firstly, an interval observer (IO) is designed to generate the state interval estimation for each agent. Secondly, an algebraic relationship is established between the system state and unknown input (UI). Thirdly, an unknown input observer (UIO) capable of generating estimates of UI and the system state has been developed through the algebraic relations. Finally, a UIO-based distributed control protocol scheme is proposed to realize the consensus of the MASs. In the end, to verify the validity of the proposed method, an example of a numerical simulation is given.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Consensus Control of Linear Parameter-Varying Multi-Agent Systems with Unknown Inputs

Zhu

Tan

2023

Sensors

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“…More particularly in applications to solve certain engineering problems such as fault detection and isolation [15], [37], [48], control of dynamical systems [17], [51], [20], control of time-delay descriptor systems [14], [20], [44], robust state reconstruction [13], [4], estimation of continuous-time switched linear systems [16], estimation of LPV systems [22], [39], estimation of nonlinear interconnected systems with time-delays [19], estimation of linear time delay systems [23], estimation of LTI systems [25], [33], state observation of LTV systems [26], [32], [41], robust observation for global Lipschitz uncertain chaotic systems [35], etc.…”

Section: Introductionmentioning

confidence: 99%

Disturbed chaotic system synchronization via nonlinear robust interval state observers

Khemiri

Tlili

2022

Preprint

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In this paper, a nonlinear interval state observer design method is synthesized for chaos synchronization between master (drive) and slave (response) systems based on the Luenberger-type observer. The stability study, analyzed with Lyapunov’s approach, is formulated in terms of linear matrix inequalities (LMIs) and subsequently to calculate the observation gain matrix. The stability of the designed state observer is analyzed within the Lyapunov approach and the LMI paradigm. Moreover, the nonlinear interval observer, comprising the lower and upper bound state observers, is used for the state reconstruction of nonlinear perturbed chaotic sys- tems subject to unknown but bounded external disturbances. The effi- ciency and high performances of the aforementioned state observer-based synchronization technique are demonstrated by a large study of numeri- cal simulation for the state synchronization of perturbed unified chaotic systems. keywords : State synchronization Nonlinear perturbed chaotic sys- tems Nonlinear interval observer Lyapunov approach LMI paradigm

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“…For the inevitable external disturbance and uncertainty of control system, many control method is used, e.g., adaptive control [7,11,17], backstepping control [7,17,18], interval observer method [19,20], sliding mode control [21][22][23]. A single control method cannot achieve the required precision of control, most of the control in the literature is the (1)…”

Section: Introductionmentioning

confidence: 99%

Variable universe adaptive fuzzy sliding mode projective synchronization of hyperjerk system based on disturbance observer

et al. 2021

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In this paper, a sliding mode projective synchronization strategy based on disturbance observer and fuzzy system is presented to implement projective synchronization of hyperjerk system with low time-varying disturbance and white noise. Theoretical analysis and numerical calculation show that the disturbance observer can approach the low time-varying disturbance very well. The application of disturbance observer reduces the chattering of the controller. Variable universe adaptive fuzzy control (VUAFC) method is utilized to further reduce the chattering phenomenon. The simulation results demonstrate the effectiveness of the proposed controller.

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Interval State Estimator Design for Linear Parameter Varying (LPV) Systems

Cited by 12 publications

References 21 publications

Consensus Control of Linear Parameter-Varying Multi-Agent Systems with Unknown Inputs

Consensus Control of Linear Parameter-Varying Multi-Agent Systems with Unknown Inputs

Disturbed chaotic system synchronization via nonlinear robust interval state observers

Variable universe adaptive fuzzy sliding mode projective synchronization of hyperjerk system based on disturbance observer

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