A sliding observer for nonlinear process control

Wang, Gow-Bin; Peng, Sheng-Shiou; Huang, Hsiao‐Ping

doi:10.1016/s0009-2509(96)00449-6

Cited by 83 publications

(42 citation statements)

References 19 publications

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“…(7)). In this study, we consider the SMO to take full advantage of its capability to deal with modeling uncertainties (8) - (10) . For a single-input single-output (SISO) nonlinear system, the SMO has the following form (particularly for the fuel injection system considered in this study):…”

Section: Injection Timing and Rate Observer Designmentioning

confidence: 99%

Development of a Sensorless Estimation Algorithm of the Injection Timing and Rate for an HSDI Common-Rail Injector

Nam

Yoon

Park

et al. 2004

JSME Int. J., Ser. C

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The performance of a common-rail fuel injection system and its effects on diesel engine combustion are strongly influenced by the injector characteristics. The injection timing and the injection rate of the common-rail injection system are important factors for combustion control and pollutant formation mechanism during the engine operation. This paper presents a dynamic model of the common-rail injector for high speed direct injection (HSDI) diesel engines and introduces a methodology for estimating the injection timing and the injection rate of the injector. The numerical simulation and the experimental results show that the proposed sliding mode observer (SMO) can effectively estimate the injection timing and the injection rate of the common-rail injector.

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Section: Injection Timing and Rate Observer Designmentioning

confidence: 99%

Development of a Sensorless Estimation Algorithm of the Injection Timing and Rate for an HSDI Common-Rail Injector

Nam

Yoon

Park

et al. 2004

JSME Int. J., Ser. C

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“…For chemical processes, SM observers have been applied for several cases. Some examples are shown in [16][17][18][19]. The idea of coupling an observer with an Observer-Based Estimator (OBE) was used in [20] and, the idea of applying a High Order Sliding Mode Observer (HOSMO) for state and parameter estimation in a Continuous StirredTank Reactor (CSTR), assuming the parameter to be estimated as an unknown input, was introduced by [21].…”

Section: Introductionmentioning

confidence: 99%

Robust Estimation for a CSTR Using a High Order Sliding Mode Observer and an Observer-Based Estimator

Botero¹,

Jiménez‐Rodríguez²,

Jaramillo³

et al. 2016

rev.ion

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This paper presents an estimation structure for a continuous stirred-tank reactor, which is comprised of a sliding mode observer-based estimator coupled with a high-order sliding-mode observer. The whole scheme allows the robust estimation of the state and some parameters, specifically the concentration of the reactive mass, the heat of reaction and the global coefficient of heat transfer, by measuring the temperature inside the reactor and the temperature inside the jacket. In order to verify the results, the convergence proof of the proposed structure is done, and numerical simulations are presented with noiseless and noisy measurements, suggesting the applicability of the posed approach. ResumenEste trabajo presenta una estructura de estimación para un reactor de tanque agitado en continuo, la cual se compone de un estimador basado en observador por modos deslizantes acoplado con un observador por modos deslizantes de alto orden. Todo el esquema permite la estimación robusta del estado y algunos parámetros, concretamente la concentración de la masa reactiva, el calor de reacción y el coeficiente global de transferencia de calor, a partir de la medición de las temperaturas al interior del reactor y de la chaqueta. Para verificar los resultados, se realizan pruebas de convergencia de la estructura propuesta, y se presentan simulaciones numéricas con mediciones ruidosas y sin ruido, lo que sugiere la aplicabilidad del enfoque planteado.Palabras clave: observadores para procesos químicos, diseño de observadores robustos, algoritmos de modos deslizantes, sistemas con incertidumbre.

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“…Concerning the state estimation, there are many works dealing with the observation techniques to estimate the state variables in chemical reactors ([4]- [11], [26]). …”

Section: Introductionmentioning

confidence: 99%

Observer-Based Input-Output Linearization Control of a Multivariable Continuous Chemical Reactor

Bouhamida¹,

Bachir²,

Mansouri³

et al. 2012

Journal of the Korean Mathematical Society

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Abstract. The goal of this paper is to develop a nonlinear observerbased control strategy for a multi-variables continuous stirred tank reactor (CSTR). A new robust nonlinear observer is constructed to estimate the whole process state variables. The observer is coupled with a nonlinear controller, designed based on the input-output linearization for controlling the concentration and reactor temperature. The closed loop system is shown to be globally asymptotically stable based on Lyapunov arguments. Finally, computer simulations are developed for showing the performance of the proposed controller.

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A sliding observer for nonlinear process control

Cited by 83 publications

References 19 publications

Development of a Sensorless Estimation Algorithm of the Injection Timing and Rate for an HSDI Common-Rail Injector

Development of a Sensorless Estimation Algorithm of the Injection Timing and Rate for an HSDI Common-Rail Injector

Robust Estimation for a CSTR Using a High Order Sliding Mode Observer and an Observer-Based Estimator

Observer-Based Input-Output Linearization Control of a Multivariable Continuous Chemical Reactor

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