Application of Nonlinear PID Controller in Main Steam Temperature Control

Gu, Junjie; Zhang, Yan-Juan; Gao, Dongdong

doi:10.1109/appeec.2009.4918186

Cited by 13 publications

(6 citation statements)

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“…Because of the longer super-heater pipe length and the larger steam volume, the superheated steam temperature control has the characteristics of large lag and large inertia [10] . The task of the superheated steam temperature control is to maintain the temperature of the outlet steam of the super-heater within the permitted range, and to ensure the temperature of the super-heater tube wall not exceeding the allowable operating temperature.…”

Section: Data-driven Pid Control For the Superheated Steam Tempementioning

confidence: 99%

Data-driven-based superheated steam temperature control of fossil fuel power generation units

Guo

Fang

2014

Proceeding of the 11th World Congress on Intelligent Control and Automation

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In modern industry, data has become an indispensible resource for the whole process of production and business. For the optimization of the control performance, the data-driven PID controller is introduced in this paper. Based on the data-driven control law, the parameters of the PID controller will be renewed automatically by using the real and historical input/output data of the plant. And then, the control action can be update in real time. From the perspective of engineering applications, the data-driven PID controller is researched as the outer loop controller in the superheated steam temperature cascade control system of fossil fuel power generation units. The simulation results show that the data-driven PID controller is suitable for the superheated steam temperature control, and its performance is better than that of the neural network PID controller.

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Section: Data-driven Pid Control For the Superheated Steam Tempementioning

confidence: 99%

Data-driven-based superheated steam temperature control of fossil fuel power generation units

Guo

Fang

2014

Proceeding of the 11th World Congress on Intelligent Control and Automation

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“…Evolutionary computation (EC) has become a common approach to solving difficult, real world problems such as optimization of functions, design of neural networks and fuzzy controllers, system identification, etc. Typical examples of EC are Genetic algorithms (GAs), Evolutionary algorithms (EAs), Simulated annealing (SA), and Taboo search (Gu, Zhang & Gao, 2009). These are able to find a global solution without any other information except the objective function.…”

Section: Optimal Tuning Of the Npid Controller Gainsmentioning

confidence: 99%

EA-Based Design of a Nonlinear PID Controller Using an Error Scaling Technique

So¹

2019

SIC

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In controller design, linear PID controllers have something of a dilemma relationship: a fast response requires large gains, which in turn, give rise to a large overshoot. For this reason, a variety of feedback control forms and related tuning methods have been implemented to guarantee satisfactory performance. Recently, multiple studies which introduce nonlinearities into the structure of the standard PID controller have been performed to solve this conflicting relationship. This study proposes an EA-based nonlinear PID controller with a first-order filter added to the derivative action to achieve the desirable quick response with low overshoot. This is realized by introducing a new type of nonlinearities in the controller gains that are time-varying functions in terms of the error and/or error rate. In addition, the nonlinear controller is designed by considering a saturation element. Then, the parameters of the nonlinear PID controller are optimally tuned by an evolutionary algorithm. In tuning the nonlinear PID controller gains, the integral of time-weighted absolute error is used as the performance evaluation of the overall control system. A set of simulation works performed on two processes with actuator saturation shows the feasibility of the proposed method.

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“…Entonces, si se introduce la función de saturación dentro del Controlador PID-C se obtiene el Controlador PID-NL que se representa en la ecuación (8). La ecuación (8) puede ser reescrita en su manera compacta usando la ecuación (9).…”

Section: Controlador Pid No Linealunclassified

“…El combinar el controlador clásico más el controlador no lineal, puede proporcionar grados de libertad adicionales para lograr un mejor rendimiento del sistema [1,2,5,9]. Las características de cambio de las funciones no lineales coinciden con el proceso de cambio ideal de los parámetros del control PID No Lineal, logrando buenos resultados de manera estática o dinámica y mejorando la calidad de control [8,3].…”

Section: Introductionunclassified

Comparación experimental de controladores PID clásico, PID no lineal y PID difuso para el caso de regulación

Natale¹,

Campos‐Mercado²,

Fernández³

et al. 2017

RCS

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Resumen. Este artículo presenta los resultados experimentales al comparar los Controladores PID Clásico, PID No Lineal y PID Difuso de Ganancias Programables usados en controladores de posición. Para la sintonización del PID clásico fue usado el segundo método de Ziegler-Nichols, el PID No Lineal fue diseñado basado en funciones de saturación con parámetros variables y el PID Difuso de Ganancias Programables fue propuesto por experiencia para minimizar el sobreimpulso. La serie de experimentos realizados mostraron que el PID Clásico presenta inestabilidad en los cambios de referencia abruptos, debido a esto se implementó el PID No Lineal con el que se logran seguir todas las referencias, presentando ligero sobreimpulso en las regiones que el control clásico se vuelve inestable, finalmente al implementar el PID Difuso se logró seguir todas las referencias sin presentar sobreimpulso y consumiendo menor cantidad de energía.

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Application of Nonlinear PID Controller in Main Steam Temperature Control

Cited by 13 publications

References 0 publications

Data-driven-based superheated steam temperature control of fossil fuel power generation units

Data-driven-based superheated steam temperature control of fossil fuel power generation units

EA-Based Design of a Nonlinear PID Controller Using an Error Scaling Technique

Comparación experimental de controladores PID clásico, PID no lineal y PID difuso para el caso de regulación

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