NSGA-II-based nonlinear PID controller tuning of greenhouse climate for reducing costs and improving performances

Hu, Haigen; Xu, Lihong; Goodman, Erik D.; Song-wei, Zeng

doi:10.1007/s00521-012-1312-8

Cited by 24 publications

(11 citation statements)

References 17 publications

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“…Fuzzy controller Process database [7,8,21,51,54]. NSGA-II is a multiobjective optimization method derived from GA with an elite preservation strategy and a fast-nondominated sorting method [7,55,56]. NSGA-II can find optimal solutions based on initial feasible solutions.…”

Section: Immune Controllermentioning

confidence: 99%

NSGA-II-Based Parameter Tuning Method and GM(1,1)-Based Development of Fuzzy Immune PID Controller for Automatic Train Operation System

Chu

Dong

et al. 2020

Mathematical Problems in Engineering

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Automatic train operation (ATO) system is one of the important components in advanced train operation control systems. Ideal controllers are expected for the automatic driving function of ATO systems. Aiming at the intelligence requirements of the systems, an NSGA-II-based parameter tuning method for the fuzzy immune PID (FI-PID) controller and a grey model GM(1,1)-based fuzzy grey immune PID (FGI-PID) controller were proposed. Taking a maglev train’s model as the control object and a velocity-time curve as the input, the feasibility of the parameter tuning method for the FI-PID controller and the applicability of the FI-PID controller and the FGI-PID controller for the ATO system were tested. The results showed that the optimized parameters were ideal, the two controllers all showed good performance on the indicators of traceability and comfort level, and the FGI-PID controller performed better than the FI-PID controller. The results exhibited the effectiveness of the proposed methods.

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Section: Immune Controllermentioning

confidence: 99%

NSGA-II-Based Parameter Tuning Method and GM(1,1)-Based Development of Fuzzy Immune PID Controller for Automatic Train Operation System

Chu

Dong

et al. 2020

Mathematical Problems in Engineering

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“…Moreover, the algorithm was also time-consuming, but in this study, the authors realised that the method of time execution could be adequate for real-time control due to the large time delay involved in greenhouse systems. Also, in Hu et al (2014), the control of climate variables was addressed using the NSGA-II. The work is similar to Hu et al (2011a), but now the optimisation functions are energy and water minimisation.…”

Section: Review Of Nabi Metaheuristics For Greenhouse Controlmentioning

confidence: 99%

Review of nature and biologically inspired metaheuristics for greenhouse environment control

Oliveira

Pires

Boaventura‐Cunha

et al. 2020

Transactions of the Institute of Measurement and Control

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A significant number of search and optimisation techniques whose principles seek inspiration from nature and biology phenomena have been proposed in the last decades. These methods have been successfully applied to solve a wide range of engineering problems. This is also the case of greenhouse environment control, which has been incorporating this type of techniques into its design. This paper addresses evolutionary and bio-inspired methods in the context of greenhouse environment control. Algorithm principles for reference techniques are reviewed, namely: simulated annealing, genetic algorithm, differential evolution and particle swarm optimisation. The last three techniques are considered using single and multiple objective formulations. A review of these algorithms within greenhouse environment control applications is presented, considering single and multiple objective problems, as well as their current trends.

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“…Los modelos que controlan las variables ambientales y el recurso hídrico se presentan de múltiples formas tanto convencionales, como modelos más rigurosos y estables [53], es decir, se evalúa sistemas de control PID [54], control moderno, control inteligente [55], entre otros, con la idea de proporcionar estabilidad en las variables de interés agrícola, la tendencia en la actualidad es a mejorar los procesos de control, partiendo de que un invernadero es un sistema no lineal multivariable [56], que requiere aplicar un manejo integral para reducir el impacto de los factores externos mantener las condiciones estables para reducir el riesgo de enfermedades, plagas, malezas y mejorar los rendimientos.…”

Section: Tendencias De La Automatización En Sistemas Irrigadosunclassified

Sistemas automatizados para el control del recurso hídrico y variables ambientales bajo invernadero: aplicaciones y tendencias

2020

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Esta revisión se propone identificar las aplicaciones más recientes relacionadas con la automatización bajo invernadero con enfoque al uso adecuado del recurso hídrico y control de variables ambientales. La revisión hace parte del proyecto de investigación aplicada, diseño e implementación de un sistema SCADA para control del recurso hídrico y variables ambientales asociadas bajo invernadero mediante PLC. Se realiza una búsqueda detallada en revistas indexadas, nacionales e internacionales, páginas web, base de datos, y empresas relacionada al sector y se clasifica la información acorde a algunos criterios diferenciados; supervisión de variables bajo invernadero en sistemas irrigados, control automático del recurso hídrico y variables ambientales, adquisición de información para irrigación bajo invernadero, tendencias de la automatización en sistemas irrigados. A partir de la información se identifican las tecnologías recientes algunas aplicaciones, las tendencias y la necesidad de aplicarlas en el sector agrícola; como aporte para reducir el impacto de la migración de la mano de obra del campo a la ciudad.

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NSGA-II-based nonlinear PID controller tuning of greenhouse climate for reducing costs and improving performances

Cited by 24 publications

References 17 publications

NSGA-II-Based Parameter Tuning Method and GM(1,1)-Based Development of Fuzzy Immune PID Controller for Automatic Train Operation System

NSGA-II-Based Parameter Tuning Method and GM(1,1)-Based Development of Fuzzy Immune PID Controller for Automatic Train Operation System

Review of nature and biologically inspired metaheuristics for greenhouse environment control

Sistemas automatizados para el control del recurso hídrico y variables ambientales bajo invernadero: aplicaciones y tendencias

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