Matching mechanism for networked control systems with multirate sampling

Jia, Xinchun; Ma, Weiwei; Yang, Fang; Zhang, Dawei

doi:10.1049/iet-cta.2017.0039

Cited by 14 publications

(9 citation statements)

References 39 publications

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“…Por su parte, Zhu et al (2016) proponen un modelo de NCS MF con retardos escasos y pérdidas de paquetes, pero esta vez desde un sistema estocástico conmutado de tiempo discreto, garantizando la estabilidad del NCS. Jia et al (2017) diseñan un controlador basado en un observador para un NCS con muestreo MF para estimar el estado del sistema en tiempo real, producto de una nueva función de Lyapunov-Krasovskii construida para analizar eficientemente el sistema de circuito cerrado en presencia de retrasos inducidos por la red que varían en el tiempo.…”

Section: E1-4unclassified

Modelo de sistema multisensor con enfoque de muestreo multifrecuencia

Yánez

Alfonsi

2021

recibe

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En la fase temprana de diseño de un multisensor están las especificaciones funcionales que establecen el comportamiento sus señales, donde es importante analizar la influencia de los tiempos de muestreo en el despliegue temporal entre los datos de entrada y salida disponibles del multisensor, como del enlace de comunicación que pudieran utilizar. Por tanto, en este trabajo se desarrolla un modelo de sistema multisensor considerando múltiples señales con periodos de muestreo que pueden ser diferentes del proceso y datos de estado, incluyendo la limitación temporal del enlace de comunicación. El sistema consta de los componentes: multisensor y estación base. Además, se desarrolló un modelo de simulación en Scilab/Xcos para ejercitar diferentes escenarios. El modelo ofrece un perfil temporal de la secuencia de datos sensoriales bajo diferentes esquemas de muestreo, permitiendo presentar la evolución de las señales con pérdidas o ausencias de muestras, las cuales al ser tratadas sistemáticamente con operadores multifrecuencia y funciones de interpolación para su reconstrucción, conducen a resultados utilizables para la abstracción del mundo real. Finalmente, la efectividad del modelo se ilustra mediante simulaciones numéricas.

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Section: E1-4unclassified

Modelo de sistema multisensor con enfoque de muestreo multifrecuencia

Yánez

Alfonsi

2021

recibe

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“…Note that (5) reflects that the dynamics of the subsystem parameterized at the larger sampling period (k is an integer multiple of q) does not change for the sampling instants corresponding to the smaller sampling period (k is not an integer multiple of q).…”

Section: A Multirate Sampling System With Two Sampling Ratesmentioning

confidence: 99%

“…In addition, this benefit increases in the case when the various input components operate at distinct fast rates. On the other hand, a matching mechanism has been investigated in [5] for networked control systems under multirate sampling while the fault-tolerant design for a class of batch networked problems has been investigated in [6] under actuator faults and external disturbances under multirate sampling and quantization effects. Furthermore, impulsive-type control in complex systems has been studied in [7] through the use of cognitive maps and multirate sampling.…”

Section: Introductionmentioning

confidence: 99%

On Some Sufficiency-Type Stability and Linear State-Feedback Stabilization Conditions for a Class of Multirate Discrete-Time Systems

Sen

2018

Mathematics

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This paper presents and discusses the stability of a discrete multirate sampling system whose sets of sampling rates (or sampling periods) are the integer multiple of those operating on all the preceding substates. Each of such substates is associated with a particular sampling rate. The sufficiency-type stability conditions are derived based on simple conditions on the norm, spectral radius and numerical radius of the matrix of the dynamics of a system parameterized at the largest sampling period.

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“…In this method, the observation rate of the output is N times slower than that of the input, and the observer is treated in the framework of a periodically time-varying system by applying the lifting method [17], [18]. An observer-based controller design problem is dealt with in [19] for a class of networked control systems with multi-rate sampling. In [20], a moving horizon estimation method of state has been studied for the case when the sampling rates of the sensors are not uniform.…”

Section: Introductionmentioning

confidence: 99%

State Observer Under Multi-Rate Sensing Environment and Its Design Using l₂-Induced Norm

2023

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Since the sensing period of a signal generally depends on the used sensor, it may be different from another, even in a single control system if it involves multiple sensors. This paper investigates a design problem of state observers for linear time-invariant discrete-time plants under a multi-rate sensing environment. The sensing periods of the sensors in the plant are assumed as mutually rational ratios. First, we characterize a state observer for a plant with multi-rate sensing as a periodically time-varying state observer. Then, we discuss the l 2 performance analysis of a state estimation error with the given periodically time-varying state observer. A linear matrix inequality (LMI) condition is provided for the analysis. By extending the LMI condition for analysis, we also provide that for multi-rate observer synthesis. Finally, we numerically illustrate the effectiveness of the proposed multi-rate state observer. Even if all the sensors have the same period, the sensing timing is not unique. Therefore, we numerically analyze whether the performance changes when the observation timing between multiple sensors is different.INDEX TERMS Multi-rate observation, state observer, linear matrix inequality, l 2 -induced norm, periodically time-varying system, multiple sensors.

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Matching mechanism for networked control systems with multirate sampling

Cited by 14 publications

References 39 publications

Modelo de sistema multisensor con enfoque de muestreo multifrecuencia

Modelo de sistema multisensor con enfoque de muestreo multifrecuencia

On Some Sufficiency-Type Stability and Linear State-Feedback Stabilization Conditions for a Class of Multirate Discrete-Time Systems

State Observer Under Multi-Rate Sensing Environment and Its Design Using l₂-Induced Norm

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Matching mechanism for networked control systems with multirate sampling

Cited by 14 publications

References 39 publications

Modelo de sistema multisensor con enfoque de muestreo multifrecuencia

Modelo de sistema multisensor con enfoque de muestreo multifrecuencia

On Some Sufficiency-Type Stability and Linear State-Feedback Stabilization Conditions for a Class of Multirate Discrete-Time Systems

State Observer Under Multi-Rate Sensing Environment and Its Design Using l2-Induced Norm

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State Observer Under Multi-Rate Sensing Environment and Its Design Using l₂-Induced Norm