Simulation of Smith fuzzy PID temperature control in enzymatic detection of pesticide residues
Keywords:
enzymatic detection, Fuzzy PID, Smith predictor, simulation, temperature controlAbstract
Enzyme activity is easily influenced by temperature, resulting in accuracy decline of enzymatic detection of pesticide residues. In this study, a controller which controls the internal temperature of the pesticide residues detector was simulated and analyzed. The mathematical model of temperature control was established by the application of the heat transfer theory. Against models with characteristics of large inertia and large hysteresis, a Smith fuzzy PID controller was proposed by combining the Smith predictor with the fuzzy PID controller. The PID controller, the fuzzy PID controller, and the Smith fuzzy PID controller were simulated in MATLAB, respectively in the same step signal given with amplitude of 1. The performance indexes (percent overshoot, settling time, and steady-state error) of various controllers were presented as follows: the PID controller (19%, 250 s, 0.0001), the fuzzy PID controller (11%, 450 s, 0.0001), and the Smith fuzzy PID controller (0%, 140 s, 0). From 1 180 s to 1 230 s, an interference signal with amplitude of 5 was added to test interference immunity. The PID controller and the fuzzy PID controller had greater fluctuations, but the Smith fuzzy PID controller had no fluctuations. The recovery time of each controller was described below: the PID controller (200 s), the fuzzy PID controller (300 s), and the Smith fuzzy PID controller (120 s). Robustness of the controller was tested by adjusting the time constant and the delay time. The performance indexes of the controllers were shown as follows: the PID controller (38%, 450 s, 0.0001), the fuzzy PID controller (23%, 880 s, 0.00025), and the Smith fuzzy PID controller (1%, 150 s, 0). The results of simulation showed that the performance indexes of the Smith fuzzy PID controller were better than that of the other controllers. Besides, the robustness and interference immunity are stronger than other controllers as well. The Smith fuzzy PID controller can accurately control the internal temperature of the pesticide residues detector to provide the best temperature for enzymatic detection. DOI: 10.3965/j.ijabe.20150801.007 Citation: Sun J, Zhang M X, Li Z M, Wu X H. Simulation of Smith fuzzy PID temperature control in enzymatic detection of pesticide residues. Int J Agric & Biol Eng, 2015; 8(1): 50-56.References
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[24] Zhang Y H. Application of Fuzzy PID-Smith cascade control in heating furnace temperature control system. Control and Instruments in Chemical Industry, 2012; 8: 979–981. (in Chinese with English abstract)
[2] Guo X S, Zhang X Y, Cai Q, Shen T, Zhu S M. Developing a novel sensitive visual screening card for rapid detection of pesticide residues in food. Food Control, 2013; 30(1): 15–23.
[3] Mishra RK, Deshpande K, Bhand S. A high-throughput enzyme assay for organophosphate residues in milk. Sensors, 2010; 10(12): 11274–11286.
[4] Campanella L, Bonanni A, Martini E, Todini N, Tomassetti M. Determination of triazine pesticides using a new enzyme inhibition tyrosinase OPEE operating in chloroform. Sensors and Actuators B: Chemical, 2005; 111-112(11): 505–514.
[5] Qiu C K, Liu X Y, Ren H Y, Jiang F. Study on detection of organophosphorus pesticide residue in vegetables by enzyme inhibition method. Food and Machinery, 2010; 26(2): 40–42. (in Chinese with English abstract)
[6] Luan Y X, H P, Lu A X, Pan L G. Detection of contamination in fruits and vegetables with a portable rapid detector. Transactions of the CSAM, 2009; 40 (Supp.): 146–149. (in Chinese with English abstract)
[7] Wang X Y, Wang X Y, Sun X, Sun D X. Optimization of determination for pesticide residues in vegetables. Transactions of the CSAM, 2008; 39(4): 97–100. (in Chinese with English abstract)
[8] Zheng Y H , Hua T C, Sun D W, Xiao J J, Xu F, Wang F F. Detection of dichlorvos residue by flow injection calorimetric biosensor based on immobilized chicken liver esterase. Journal of Food Engineering, 2006; 74(1): 24–29.
[9] Llopis X, Pumera M, Alegret S, Merkoci A. Lab-on-a-chip for ultrasensitive detection of carbofuran by enzymatic inhibition with replacement of enzyme using magnetic beads. Lab on a Chip, 2009; 9(2): 213–218.
[10] Valdes-Ramirez G, Fournier D, Ramirez-Silva M T, Marty J L. Sensitive amperometric biosensor for dichlorovos quantification: Application to detection of residues on apple skin. Talanta, 2008; 74(4): 741–746.
[11] Qiu Z J, Lu J Ff, He Y. Rapid detection system development and influence factor analysis for pesticide residues in agricultural products by enzyme inhibition method. Transactions of the CSAE, 2007; 23(9): 229–233. (in Chinese with English abstract)
[12] Yang H, Jin W, Wang L L, Su M W, Zheng Y B, Lu X H. A New hand-held pesticide residue monitor instrument with temperature correction function. Chinese Journal of Analytical Chemistry, 2005; 33(7): 1041–1044. (in Chinese with English abstract)
[13] Li L, Zhu L, Jiang Q, Zhang M. Simulation of temperature control algorithm in micro flow-through PCR system. Transactions of the CSAM, 2012; 43(Supp.): 295–299. (in Chinese with English abstract)
[14] Fu L S, Sun X J, Wu X H, Piao Z L, Hai P. Application of fuzzy adaptive PID controller in solar drying temperature control. Transactions of the CSAE, 2006; 22(7): 217–219. (in Chinese with English abstract)
[15] Zhou L Y, Zhao G S. Application of fuzzy-PID control algorithm in uniform velocity temperature control system of resistance furnace. Chinese Journal of Scientific Instrument, 2008; 29(2): 405–409. (in Chinese with English abstract)
[16] Du R C, Gong B C, Liu N N, Wang C C, Yang Z D, Ma M J. Design and experiment on intelligent fuzzy monitoring system for corn planters. Int J Agric & Biol Eng, 2013; 6(3): 11-18.
[17] Wang B Z, Song D F, Liu W F. Improved PID control based on Smith predictive compensation and RBF neural network. Modern Electronics Technique, 2011; 34(5): 153–157.
[18] Lin D L, Shen E D, Zhang K Y, Yu L W. Greenhouse control using geothermal water heating system. Transactions of the CSAM, 2009; 40(2): 151–154, 219. (in Chinese with English abstract)
[19] Pang L P, Wang J, Liu W K. Application of predictive fuzzy-PID in center air adjusting control system. Journal of Beijing University of Aeronautics and Astronautics, 2004; 30(8): 757–761. (in Chinese with English abstract)
[20] Qin S, Gong Y, Yuan W Q, Yang H J. High precision temperature control for projection lens with long time thermal response constant. Optics and Precision Engineering, 2013; 21(1): 108–114. (in Chinese with English abstract)
[21] Chen L. Medical thermostat temperature control system. Beijing: Beijing Jiaotong University, 2007. (in Chinese with English abstract)
[22] Xiao J M, Zhu H M, Jiao L Y, Zhang R. Based on Fuzzy -PID self-tuning temperature control system of the furnace. 2011 International Conference on Electric Information and Control Engineering, 2011; 1203–1206.
[23] Shan C X, Chen W J, Peng J. Design and simulation of temperature control system of heating exchanging station based on fuzzy PID control. Instrument Technique and Sensor, 2011; 9: 79–82. (in Chinese with English abstract)
[24] Zhang Y H. Application of Fuzzy PID-Smith cascade control in heating furnace temperature control system. Control and Instruments in Chemical Industry, 2012; 8: 979–981. (in Chinese with English abstract)
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Published
2015-02-28
How to Cite
Jun, S., Meixia, Z., Zhengming, L., & Xiaohong, W. (2015). Simulation of Smith fuzzy PID temperature control in enzymatic detection of pesticide residues. International Journal of Agricultural and Biological Engineering, 8(1), 50–56. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/1053
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Information Technology, Sensors and Control Systems
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