Pole-placement self-tuning control of nonlinear Hammerstein system and its application to pH process control

Zou, Zhiyun; Zhao, Ding; Liu, Xinghong; Guo, Yongan; Guan, Chen; Feng, Wenqiang; Guo, Ning

doi:10.1016/j.cjche.2015.01.009

Cited by 12 publications

(9 citation statements)

References 17 publications

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“…Soda is 0.1 mol ⋅ L −1 NaCO 3 and Acid is 0.1 mol ⋅ L −1 HCL. The dynamic of every pilot plant PH process can be described with the Hammerstein model as follows 39 :…”

Section: Realistic Ph Process Examplementioning

confidence: 99%

“…Soda is 0.1

mol\cdot {L}^{-1}

NaCO 3 and Acid is 0.1

mol\cdot {L}^{-1}

HCL. The dynamic of every pilot plant PH process can be described with the Hammerstein model as follows 39 :

x(kT)=u(kT)-1.207{u}^2(kT)+1.15{u}^3(kT)\left(1-1.558{z}^{-1}+0.597{z}^{-2}\right)\mathrm{y}(kT)=

{z}^{-1}\left(0.01849{z}^{-1}+0.01728{z}^{-2}+0.00248{z}^{-3}\right)x(kT).

where

x(kT)

is the nonlinear basis function,

u(kT)={u}_m(kT)-{u}_s

and

y (kT) = y_{m} (kT<...

…”

Section: Simulationmentioning

confidence: 99%

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Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Wang

et al. 2022

Intl J Robust & Nonlinear

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A distributed event-triggered data-based control protocol is proposed for a class of unknown nonlinear heterogeneous multi-agent systems (MASs) to address consistent reference signal tracking issue subject to the limited communication bandwidth. First, an event-triggering condition that only relies on local output data of each agent is designed, and the event-triggered communication between different agents depends on this condition. Second, agent models are constructed dynamically using dynamic linearization technology. Third, a novel distributed data-driven control strategy based on event-triggered communication mechanism is designed for heterogeneous agents to realize consistent desired trajectory tracking mission under switching topologies. The proposed control protocol is characterized by the information transmission of each agent in a fully intermittent manner without any global I/O (Input and Output) data. On this basis, convergence performance is analyzed using the principle of compressed mapping. Results showed that the tracking error of all agents is uniformly bounded. Effectiveness of the proposed method is verified through two numerical experiments.

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“…Soda is 0.1 mol ⋅ L −1 NaCO 3 and Acid is 0.1 mol ⋅ L −1 HCL. The dynamic of every pilot plant PH process can be described with the Hammerstein model as follows 39 :…”

Section: Realistic Ph Process Examplementioning

confidence: 99%

“…Soda is 0.1

mol\cdot {L}^{-1}

NaCO 3 and Acid is 0.1

mol\cdot {L}^{-1}

HCL. The dynamic of every pilot plant PH process can be described with the Hammerstein model as follows 39 :

x(kT)=u(kT)-1.207{u}^2(kT)+1.15{u}^3(kT)\left(1-1.558{z}^{-1}+0.597{z}^{-2}\right)\mathrm{y}(kT)=

{z}^{-1}\left(0.01849{z}^{-1}+0.01728{z}^{-2}+0.00248{z}^{-3}\right)x(kT).

where

x(kT)

is the nonlinear basis function,

u(kT)={u}_m(kT)-{u}_s

and

y (kT) = y_{m} (kT<...

…”

Section: Simulationmentioning

confidence: 99%

Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Wang

et al. 2022

Intl J Robust & Nonlinear

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“…e Hammerstein model is a typical nonlinear model composed of static nonlinear links and dynamic linear links. It can reflect the characteristics of process characteristics and describe a series of nonlinear processes such as neutralization processes [8,9], lithium-ion battery thermal systems [10,11], heat dissipation systems [12], and so on.…”

Section: Introductionmentioning

confidence: 99%

Recursive Identification for Fractional Order Hammerstein Model Based on ADELS

Jin

Cai

et al. 2021

Mathematical Problems in Engineering

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This paper deals with the identification of the fractional order Hammerstein model by using proposed adaptive differential evolution with the Local search strategy (ADELS) algorithm with the steepest descent method and the overparameterization based auxiliary model recursive least squares (OAMRLS) algorithm. The parameters of the static nonlinear block and the dynamic linear block of the model are all unknown, including the fractional order. The initial value of the parameter is obtained by the proposed ADELS algorithm. The main innovation of ADELS is to adaptively generate the next generation based on the fitness function value within the population through scoring rules and introduce Chebyshev mapping into the newly generated population for local search. Based on the steepest descent method, the fractional order identification using initial values is derived. The remaining parameters are derived through the OAMRLS algorithm. With the initial value obtained by ADELS, the identification result of the algorithm is more accurate. The simulation results illustrate the significance of the proposed algorithm.

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“…Se comparadas aos modelos de Volterra e bilinear, as estruturas de Hammerstein e de Wiener apresentam como vantagem adicional a simplicidade das suas representações (Haryanto e Hong, 2013;Mzyk, 2014). Além disso, tais estruturas foram usadas com sucesso para representar sistemas não lineares em diversas aplicações práticas na área de processos químicos (Zou et al, 2015), biológicos (Jalaleddini e Kearney, 2013;Abedini Najafabadi e Shahrokhi, 2016;Narayanan et al, 2017) e de controle (Gao et al, 2015;Zhang et al, 2017).…”

Section: Introdu ç ãOunclassified

Nova Abordagem para Linearização de Modelos de Hammerstein Identificados por Métodos de Subespaço

Santos

Braga

Ricco

2021

Procedings Do XV Simpósio Brasileiro De Automação Inteligente

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The quality of the model is an impacting factor on the accuracy and response speed of a control system. To maintain the trade-off between model and controller complexity, the use of interconnected blocks in the Hammerstein structure is an interesting alternative. The motivation is that linearizing such models allows the use of classical control techniques in a wider range of process operation. After several tests performed in this work, it was observed that static functional functions in small process operating ranges are not effective as described in the literature. Therefore, this paper proposes, by means of algebraic manipulations, the use of an algebraic inverse of the static curve estimated for the Hammerstein model. In the first approach, the static curve and the linear block are estimated in one step. In the second, each of the plots is estimated in two steps. The numerical results suggest that the algebraic inverse coupled with the two-step methodology provides greater accuracy in control, however a detailed feasibility analysis should be done in each case. Resumo: A qualidade do modelo é um fator impactante na precisão e velocidade de resposta de um sistema de controle. Para manter o compromisso entre a complexidade do modelo e do controlador, o uso de blocos interconectados na estrutura de Hammerstein é uma alternativa interessante. A motivação é que linearizar tais modelos permite o uso de técnicas clássicas de controle em uma faixa mais ampla de operação do processo. Após vários testes realizados neste trabalho, observou-se que funções estáticas funcionais em pequenas faixas de operação do processo não são eficazes como descrito na literatura. Sendo assim, este trabalho propõe, por meio de manipulações algébricas, o uso de uma inversa algébrica da curva estática estimada para o modelo de Hammerstein. Na primeira abordagem, a curva estática e o bloco linear são estimados em uma etapa. Na segunda, estima-se cada uma das parcelas em duas etapas. Os resultados numéricos sugerem que a inversa algébrica aliada à metodologia em duas etapas proporcionam maior precisão no controle, todavia uma análise detalhada de viabilidade deve ser feita em cada caso.

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Pole-placement self-tuning control of nonlinear Hammerstein system and its application to pH process control

Cited by 12 publications

References 17 publications

Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Event‐triggered model‐free adaptive consensus tracking control for nonlinear multi‐agent systems under switching topologies

Recursive Identification for Fractional Order Hammerstein Model Based on ADELS

Nova Abordagem para Linearização de Modelos de Hammerstein Identificados por Métodos de Subespaço

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