Event-triggered policy for dynamic output stabilization of discrete-time LPV systems under input constraints

Souza, Carla de; Leite, Valter J. S.; Tarbouriech, Sophie; Castelan, Eugênio B.

doi:10.1016/j.sysconle.2021.104950

Cited by 15 publications

(15 citation statements)

References 36 publications

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“…As these matrices acts as weights on the terms of the event-triggering condition, their computation has a direct impact on the event-triggering policy and, consequently, on the way of reducing the data transmissions. Note that such an event-triggering rule is more involving than those considered, for instance, in [7], [12], [22], due to the parameter dependence of the weighting matrices.…”

Section: B Event-triggered Schemementioning

confidence: 99%

“…Concerning the transmission rate, the worst case is reached with g = 1, which leads to a 100% transmission rate. Therefore, g = 1 implies that the controller shares the same scheduling parameter of the plant, then recovering the assumption of parameter sharing in [7], [8], [19], [22].…”

Section: B Event-triggered Schemementioning

confidence: 99%

“…Let us emphasize that the presence of input saturation needs to characterize the region of attraction of the origin for the closed loop [26]. Due to the fact that we do not assume any stability hypothesis for the open loop, we are interested by the regional asymptotic stability of the closed-loop system and therefore the region of attraction will not be the whole state space [20], [13], [7]. As the exact characterization of such a region is extremely challenging, a workaround consists in characterizing an estimate of the domain of attraction of the origin for the closed-loop system (6).…”

Section: B Event-triggered Schemementioning

confidence: 99%

“…This section aims to propose an optimization procedure that indirectly reduces the number of state signal updates. By looking at the event-triggering condition (7), we can see that it is a relative measure of the deviation between the last sampled state and the current state with Q ∆i and Q xi acting as weights on this measure. Thus, we have that the "smaller" Q ∆i and the "larger" Q xi are, the more the current state is allowed to deviate from the last sampled one and the fewer transmissions events are expected.…”

Section: A Optimization Proceduresmentioning

confidence: 99%

“…The static and dynamic feedback controllers were designed in [9] to investigate the event-triggered control of discrete-time linear systems subject to actuator saturation. However, the eventtriggered control of discrete-time LPV systems with saturating actuators has not been widely explored in the literature (see [7], [8], for example). In particular, the case where the plant and the controller do not share the same scheduling parameters consists of a relevant gap in the literature.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Direct Parameter-Error Codesign Approach of Discrete-Time Saturated LPV Systems

Souza

Leite

Tarbouriech

et al. 2022

IEEE Trans. Automat. Contr.

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Considering a discrete-time linear parametervarying (LPV) systems with input constraints, the paper deals with the co-design of a parameter-dependent statefeedback controller and a new parameter-dependent eventtriggering mechanism. Two independent event-triggering policies are introduced at the sensor node to economize the limited network resources. They indicate whether the current state or the current scheduling parameters should be transmitted to the controller or not. In this sense, the controller scheduling parameters can differ from those of the system, yielding a certain degree of robustness concerning parameter deviations. Sufficient conditions, given in terms of linear matrix inequalities (LMIs), ensure the regional asymptotic stability of the closed loop. To formulated them, we use the Lyapunov theory along with the generalized sector condition. Moreover, we formulate a convex optimization procedure indirectly reducing the transmission activity over the network. The proposed methodology effectiveness is attested through numerical examples and comparisons with related works from the literature.

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Section: B Event-triggered Schemementioning

confidence: 99%

Section: B Event-triggered Schemementioning

confidence: 99%

Section: B Event-triggered Schemementioning

confidence: 99%

Section: A Optimization Proceduresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Direct Parameter-Error Codesign Approach of Discrete-Time Saturated LPV Systems

Souza

Leite

Tarbouriech

et al. 2022

IEEE Trans. Automat. Contr.

Self Cite

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Stabilization and disturbance rejection with decay rate bounding in discrete‐time linear parameter‐varying systems via ℋ_∞gain‐scheduling static output feedback control

Sereni

Assunção

Teixeira

2022

Intl J Robust & Nonlinear

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The stabilization of discrete‐time linear parameter‐varying (LPV) systems via gain‐scheduling static output feedback (SOF) control is addressed in this article. We propose new sufficient linear matrix inequalities (LMI) conditions for synthesizing a gain‐scheduled SOF controller that ensures asymptotic stability and also imposes a lower bound on the closed‐loop decay rate. The SOF controller design is based on a two‐step method: a state‐feedback controller is obtained in a first‐stage design, which is then used as input information in the second stage for computing the desired gain‐scheduled SOF controller. The proposed LMI constraints are given in terms of the existence of affine parameter‐dependent Lyapunov functions, considering arbitrarily fast variation of the time‐varying parameters. An extension for coping with disturbance rejection is also proposed, in terms of the scriptH∞$$ {\mathcal{H}}_{\infty } $$ guaranteed cost optimization. Some numerical experiments are presented to illustrate the control synthesis procedure and its efficacy. Also, feasibility analyses are presented to compare and show the advantages of our results over other available strategies present in literature.

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Finite‐time fault detection for discrete nonlinear systems with time‐varying delays under the dynamic event‐triggered mechanism

Chen

et al. 2022

Intl J Robust & Nonlinear

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This article is concerned with the finite‐time fault detection (FTFD) problem for discrete networked systems subject to nonlinearities and time‐varying delays under the dynamic event‐triggered mechanism. The dynamic event‐based communication scheme is adopted to improve the efficiency of the bandwidth utilization, reduce the transmission of redundant signals and decrease the transmission pressure of the network. Then, by constructing a new Lyapunov functional and utilizing the appropriate inequality techniques, some sufficient conditions are derived under which the addressed augmented system achieves the finite‐time stability and attains a satisfactory H∞$$ {H}_{\infty } $$ performance index. Additionally, the expression forms of the fault detection filter (FDF) parameters are presented based on the solutions to certain matrix inequalities. In the end, a numerical simulation is employed to demonstrate the effectiveness and feasibility of the proposed FTFD strategy.

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Event-triggered policy for dynamic output stabilization of discrete-time LPV systems under input constraints

Cited by 15 publications

References 36 publications

A Direct Parameter-Error Codesign Approach of Discrete-Time Saturated LPV Systems

A Direct Parameter-Error Codesign Approach of Discrete-Time Saturated LPV Systems

Stabilization and disturbance rejection with decay rate bounding in discrete‐time linear parameter‐varying systems via ℋ_∞gain‐scheduling static output feedback control

Finite‐time fault detection for discrete nonlinear systems with time‐varying delays under the dynamic event‐triggered mechanism

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Event-triggered policy for dynamic output stabilization of discrete-time LPV systems under input constraints

Cited by 15 publications

References 36 publications

A Direct Parameter-Error Codesign Approach of Discrete-Time Saturated LPV Systems

A Direct Parameter-Error Codesign Approach of Discrete-Time Saturated LPV Systems

Stabilization and disturbance rejection with decay rate bounding in discrete‐time linear parameter‐varying systems via ℋ∞gain‐scheduling static output feedback control

Finite‐time fault detection for discrete nonlinear systems with time‐varying delays under the dynamic event‐triggered mechanism

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Stabilization and disturbance rejection with decay rate bounding in discrete‐time linear parameter‐varying systems via ℋ_∞gain‐scheduling static output feedback control