Fuzzy-PID Strategy Based on PSO Optimization for pH Control in Water and Fertilizer Integration

Fu, Changxin; Ma, Xin; Zhang, Lixin

doi:10.1109/access.2021.3138910

Cited by 15 publications

(8 citation statements)

References 28 publications

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“…In the actual fertilization process, the fertilizer mother liquor and irrigation water are added to the mixing tank first, and the pH value measured at this time is alkaline, then the acid tank solenoid valve is opened, and the pH value in the mixing tank is made to meet the requirements for cotton growth by controlling the opening time of the acid tank solenoid valve. An extensive literature review revealed that the most suitable pH values for cotton growth are between 6 and 7 [13].The process of mixing mother liquor, acid and irrigation water can be regarded as the process of acid-base neutralization [12].This process can consist of a dynamic equation describing the state variables and a static pH equation describing the neutralization titration. Assume that the volume V of the liquid before and after mixing in the mixing tank remains the same, and the mother liquor, water and acid are mixed uniformly.…”

Section: Description Of Water and Fertilizer Ph Adjustment Process An...mentioning

confidence: 99%

“…According to the mathematical model of the cotton field fertilization irrigation system, the corresponding parameters were brought into the equation (12). The coefficients of the PID were adjusted by trial-and-error method so that the error between the set amount and the feedback amount was reduced until the system requirements were…”

Section: 2design Of Fuzzy Pid Controller Based On Genetic Algorithm O...mentioning

confidence: 99%

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Research on water and fertilizer PH control strategy of automatic fertilizer application system in cotton field

Wang

Zhang

et al. 2023

Preprint

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Xinjiang, China's largest cotton-producing region, suffers from a severe shortage of water resources. Cotton is a highly adapted crop to limited water conditions and no significant decreases in cotton yield have been observed under appropriate limited water conditions. Therefore, water and fertilizer integration technology has become the fundamental way out for the development of the cotton industry in Xinjiang. Time-varying, hysteresis and non-linearity in automatic fertilizer application systems for cotton fields. To address this problem, a fuzzy PID controller based on genetic algorithm optimisation is studied and designed in this paper. Optimisation of the control parameters of the PID is achieved through the optimisation of the proportionality factor in the fuzzy control algorithm by means of a genetic algorithm to complete the precise control of the fertilizer pH value. Development of an automatic fertilizer control system based on a real-time fuzzy control system using MATLAB and PLC controllers with OPC technology. The performance of the controller was verified experimentally and the results showed that the controller has good control accuracy and robustness compared with conventional PID controllers and fuzzy PID controllers, achieving the effect of precise fertilizer application.

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Section: Description Of Water and Fertilizer Ph Adjustment Process An...mentioning

confidence: 99%

Section: 2design Of Fuzzy Pid Controller Based On Genetic Algorithm O...mentioning

confidence: 99%

Research on water and fertilizer PH control strategy of automatic fertilizer application system in cotton field

Wang

Zhang

et al. 2023

Preprint

Self Cite

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show abstract

“…The integration of water and fertilizer is a highly efficient and water-saving agricultural technology recognized in today's world. It mainly supplies water and fertilizer to crops accurately, regularly, and quantitatively at the same time by using irrigation equipment according to soil characteristics and crop growth rule 18 . Irrigation fertilization is a progressive fertilization technique that can replenish water and fertilizer to the crop at regular intervals, thus promoting the uptake of water and fertilizer by the crop 19 .…”

Section: Related Workmentioning

confidence: 99%

Parameter optimization of PID controller for water and fertilizer control system based on partial attraction adaptive firefly algorithm

Huang

Tian

Liu

et al. 2022

Sci Rep

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Proportional Integral Derivative (PID) control is the main control method in the process of agricultural water and fertilizer regulation, and its parameter setting directly affects the control effect of water and fertilizer regulation. However, the traditional PID parameters are adjusted manually such as using the critical proportionality method, which is time-consuming and difficult to achieve optimal control effects. To solve the optimal combination of PID control parameters and improve the control effect of water and fertilizer regulation, a partial attraction adaptive firefly algorithm (PAAFA) is proposed in this paper. Specifically, a partial attraction strategy is designed to speed up the convergence of the PAAFA and reduce the oscillation problem at the late stage of the algorithm. In addition, an adaptive inertia weight operator is proposed to balance the global search capability and local search capability of PAAFA and avoid the algorithm from trapping in the local optimum. Subsequently, to test the performance of PAAFA, the algorithm is subjected to a series of simulation experiments and bench tests with the latest methods, i.e., genetic algorithm (GA), Adaptive genetic algorithm (AGA), and firefly algorithm (FA) applied to PID parameter optimization problems. The simulation results demonstrate that the regulation times of the response curve of PAAFA-based PID control are reduced by 22.75%,10.10%and 20.61%, respectively, compared with GA, AGA, and FA. The bench test results show that the PAAFA-based PID control has the smallest relative error, and best control accuracy compared to GA, AGA, and FA, with an average relative error reduction of 3.99, 2.42, and 3.50 percentage points respectively.

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“…The number of trigger links generated by R-Backdoor is consistent with the number of trigger links of Link-Backdoor. • PSO-Backdoor (P-Backdoor): It utilizes particle swarm optimization [8] to modify the injection nodes features of the trigger and structure of trigger. We adopt a population size of 200, 50 iterations per round and learning factors of 0.5 and 1.5 in the experiment.…”

Section: Baselinesmentioning

confidence: 99%

Link-Backdoor: Backdoor Attack on Link Prediction via Node Injection

Zheng¹,

Xiong²,

Ma³

et al. 2022

Preprint

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Link prediction, inferring the undiscovered or potential links of the graph, is widely applied in the real-world. By facilitating labeled links of the graph as the training data, numerous deep learning based link prediction methods have been studied, which have dominant prediction accuracy compared with non-deep methods. However, the threats of maliciously crafted training graph will leave a specific backdoor in the deep model, thus when some specific examples are fed into the model, it will make wrong prediction, defined as backdoor attack. It is an important aspect that has been overlooked in the current literature. In this paper, we prompt the concept of backdoor attack on link prediction, and propose Link-Backdoor to reveal the training vulnerability of the existing link prediction methods. Specifically, the Link-Backdoor combines the fake nodes with the nodes of the target link to form a trigger. Moreover, it optimizes the trigger by the gradient information from the target model. Consequently, the link prediction model trained on the backdoored dataset will predict the link with trigger to the target state. Extensive experiments on five benchmark datasets and five well-performing link prediction models demonstrate that the Link-Backdoor achieves the state-of-the-art attack success rate under both white-box (i.e., available of the target model parameter) and black-box (i.e., unavailable of the target model parameter) scenarios. Additionally, we testify the attack under defensive

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Fuzzy-PID Strategy Based on PSO Optimization for pH Control in Water and Fertilizer Integration

Cited by 15 publications

References 28 publications

Research on water and fertilizer PH control strategy of automatic fertilizer application system in cotton field

Research on water and fertilizer PH control strategy of automatic fertilizer application system in cotton field

Parameter optimization of PID controller for water and fertilizer control system based on partial attraction adaptive firefly algorithm

Link-Backdoor: Backdoor Attack on Link Prediction via Node Injection

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