Adaptive Fuzzy Control of a Class of MIMO Nonlinear System With Actuator Saturation for Greenhouse Climate Control Problem

Su, Yuanping; Xu, Lihong; Li, Dawei

doi:10.1109/tase.2015.2392161

Cited by 52 publications

(22 citation statements)

References 24 publications

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“…Although we have developed an adaptive fuzzy control approach (AFC) for greenhouse climate control in previous work, the energy saving performance of greenhouse climate control still needs to be further improved. Therefore, it is the motivation of this work to develop an optimal control approach for greenhouse climate.…”

Section: Resultsmentioning

confidence: 99%

“…A commercial greenhouse must create a suitable environment by regulating the greenhouse microclimate to increase crop growth, thereby allowing an increase in the income of the grower, so long as the associated costs are not excessive. In recent years, many approaches have been proposed to address the greenhouse climate control problem . Various control theories, including logical control, fuzzy control, predictive control, neural network (NN) control, PID control, etc, have been introduced to solve this problem.…”

Section: Introductionmentioning

confidence: 99%

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Nearly dynamic programming NN‐approximation–based optimal control for greenhouse climate: A simulation study

Goodman

2017

Optim Control Appl Methods

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Summary Greenhouse production must create a suitable growth environment for its crop to improve yield while minimizing the energy used to maintain the greenhouse environment, thereby reducing production cost. To this end, this paper develops a nearly optimal control approach based on adaptive dynamic programming. In this method, 3 neural networks are used to estimate the value function and control policy and to compensate for the unmodeled dynamics of the greenhouse climate. Taking into account the greenhouse system typically being an overactuated system, the total control efforts for heat, fog, and CO2 are considered as the virtual control inputs to be generated by the optimal controller. To obtain the real control inputs, a control allocation technique is introduced to distribute the virtual control inputs to the actuators. Finally, Lyapunov stability analysis is performed to derive the update law of the neural networks to ensure the asymptotic convergence of the closed‐loop system, and simulation is carried out to illustrate the effectiveness and control performance of the proposed approach.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Nearly dynamic programming NN‐approximation–based optimal control for greenhouse climate: A simulation study

Goodman

2017

Optim Control Appl Methods

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“…Gupta and Chandra [3] studied the effect of various energy conservation measures to arrive at a set of design features for an energy efficient greenhouse. Su et al [4] used fuzzy logic systems to track the temperature and humidity in the greenhouse. Spanomitsios [5] studied the efficiency and estimation of energy consumption in thin film greenhouses under different strategies.…”

Section: Introductionmentioning

confidence: 99%

Energy Consumption Prediction of a Greenhouse and Optimization of Daily Average Temperature

Shen

Wei

2018

Energies

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Greenhouses are high energy-consuming and anti-seasonal production facilities. In some cases, energy consumption in greenhouses accounts for 50% of the cost of greenhouse production. The high energy consumption has become a major factor hindering the development of greenhouses. In order to improve the energy efficiency of the greenhouse, it is important to predict its energy consumption. In this study, the energy consumption mathematical model of a Venlo greenhouse is established based on the principle of energy conservation. Three optimization algorithms are used to identify the parameters which are difficult to determine in the energy consumption model. In order to examine the accuracy of the model, some verifications are made. The goal of achieving high yield, high quality and high efficiency production is a problem in the study of greenhouse environment control. Combining the prediction model of greenhouse energy consumption with the relatively accurate weather forecast data for the next week, the energy consumption of greenhouse under different weather conditions is predicted. Taking the minimum energy consumption as the objective function, the indoor daily average temperatures of 7 days are optimized to provide the theoretical reference for the decision-making of heating in the greenhouse. The results show that the optimized average daily temperatures save 9% of the energy cost during a cold wave.

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“…Based on implicit function theorem, the first category uses either a fuzzy logic system or a neural network to estimate the ideal control action directly. In the second category, indirect control scheme uses fuzzy logic to estimate the plant dynamics and then synthesizes a control law based on these estimations [14].…”

Section: Introductionmentioning

confidence: 99%

Experimental Evaluation and Implementation of Adaptive Fuzzy Controller for SISO Nonlinear System

2017

IJMTER

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Abstract-In this paper design method for adaptive fuzzy controller is proposed and it is applied to the non-linear system called CSTR. The control objective is to implement output tracking control on nonlinear systems. Fuzzy logic system is introduced to estimate the unknown nonlinearity. By using fuzzy rules, estimation error and external disturbances are well handled. This gives us a guarantee of the stability when we track the control process. The control gain estimation is obtained by fuzzy logic system. Later Lyapunov stability analysis is performed and evaluated. To validate the proposed control scheme we apply it to continuous stirred tank reactor. The gains for PID controller are estimated from fuzzy logic system. The simulation exhibits satisfactory results, in which temperature is controlled.

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Adaptive Fuzzy Control of a Class of MIMO Nonlinear System With Actuator Saturation for Greenhouse Climate Control Problem

Cited by 52 publications

References 24 publications

Nearly dynamic programming NN‐approximation–based optimal control for greenhouse climate: A simulation study

Nearly dynamic programming NN‐approximation–based optimal control for greenhouse climate: A simulation study

Energy Consumption Prediction of a Greenhouse and Optimization of Daily Average Temperature

Experimental Evaluation and Implementation of Adaptive Fuzzy Controller for SISO Nonlinear System

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