An Improved Cooperative Team Spraying Control of a Diffusion Process With a Moving or Static Pollution Source

Juan Chen; Baotong Cui; YangQuan Chen; Bo Zhuang

doi:10.1109/JAS.2019.1911519

Volume 7 Issue 2

Mar. 2020

IEEE/CAA Journal of Automatica Sinica

JCR Impact Factor: 15.3, Top 1 (SCI Q1)

CiteScore: 23.5, Top 2% (Q1)
Google Scholar h5-index: 77， TOP 5

Turn off MathJax

Article Contents

Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2020 > 7(2): 494-504

Juan Chen, Baotong Cui, YangQuan Chen and Bo Zhuang, "An Improved Cooperative Team Spraying Control of a Diffusion Process With a Moving or Static Pollution Source," IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 494-504, Mar. 2020. doi: 10.1109/JAS.2019.1911519

Citation:

Juan Chen, Baotong Cui, YangQuan Chen and Bo Zhuang, "An Improved Cooperative Team Spraying Control of a Diffusion Process With a Moving or Static Pollution Source," IEEE/CAA J. Autom. Sinica, vol. 7, no. 2, pp. 494-504, Mar. 2020. doi: 10.1109/JAS.2019.1911519

Citation:

PDF( 1181 KB)

An Improved Cooperative Team Spraying Control of a Diffusion Process With a Moving or Static Pollution Source

doi: 10.1109/JAS.2019.1911519

Funds: This work was partially supported by the National Natural Science Foundation of China (61473136, 61807016), the Fundamental Research Funds for the Central Universities (JUSRP51322B), the 111 Project (B12018), and Jiangsu Innovation Program for Graduates (KYLX15 1170)

More Information

Author Bio:
Juan Chen received the Ph.D. degree in control science and engineering from the School of IoT Engineering, Jiangnan University in 2011. She joined the Mechatronics, Embedded Systems and Automation (MESA) Laboratory of the University of California, Merced, USA as an exchange Ph.D. student hosted by Prof. YangQuan Chen from March 2015 to September 2015. She is a Post-doctoral Fellow at Tallinn University of Technology, Estonia, since December 2018. Her research interests include control of diffusion systems, boundary control and boundary observer design of fractional distributed parameter systems

Baotong Cui received the Ph.D. degree in control theory and control engineering from the College of Automation Science and Engineering, South China University of Technology, in July 2003. He was a Post-doctoral Fellow at Shanghai JiaoTong University, from July 2003 to September 2005, and a visiting scholar in Department of Electrical and Computer Engineering, National University of Singapore, Singapore, from August 2007 to February 2008. He joined Jiangnan University, China, in 2003, where he is a Full Professor for the School of IoT Engineering. His research interests include systems analysis, control of distributed parameter systems, and stability of dynamical systems

YangQuan Chen (M’95–SM’98) received the Ph.D. degree in advanced control and instrumentation from Nanyang Technological University, Singapore, in 1998. Dr. Chen was on the Faculty of Electrical and Computer Engineering at Utah State University before he joined the School of Engineering, University of California, Merced in 2012 where he teaches “Mechatronics” for juniors and “Fractional Order Mechanics” for graduates. His research interests include mechatronics for sustainability, cognitive process control and hybrid lighting control, multi-UAV based cooperative multi-spectral “personal remote sensing” and applications, applied fractional calculus in controls, signal processing and energy informatics, distributed measurement and distributed control of distributed parameter systems using mobile actuator and sensor networks

Bo Zhuang is a Ph.D. candidate at the School of IoT Engineering of Jiangnan University. He joined the MESA Laboratory of the University of California, Merced, USA as an exchange Ph.D. student hosted by Prof. YangQuan Chen from December 2015 to June 2016. He is also an Associate Professor at Binzhou University. His research interests include analysis and control of distributed parameter systems, mobile agents, and coverage optimization
Corresponding author: J. Chen, B. T. Cui, and B. Zhuang are with the Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) and School of IoT Engineering, Jiangnan University, Wuxi 214122, China (e-mail: karenchenjuan.student@sina.com; btcui@jiangnan.edu.cn; bozhuang@jiangnan.edu.cn)
Received Date: 2018-07-25
Accepted Date: 2018-11-02

Abstract

Abstract

This paper is concerned with a control problem of a diffusion process with the help of static mesh sensor networks in a certain region of interest and a team of networked mobile actuators carrying chemical neutralizers. The major contribution of this paper can be divided into three parts: the first is the construction of a cyber-physical system framework based on centroidal Voronoi tessellations (CVTs), the second is the convergence analysis of the actuators location, and the last is a novel proportional integral (PI) control method for actuator motion planning and neutralizing control (e.g., spraying) of a diffusion process with a moving or static pollution source, which is more effective than a proportional (P) control method. An optimal spraying control cost function is constructed. Then, the minimization problem of the spraying amount is addressed. Moreover, a new CVT algorithm based on the novel PI control method, henceforth called PI-CVT algorithm, is introduced together with the convergence analysis of the actuators location via a PI control law. Finally, a modified simulation platform called diffusion-mobile-actuators-sensors-2-dimension-proportional integral derivative (Diff-MAS2D-PID) is illustrated. In addition, a numerical simulation example for the diffusion process is presented to verify the effectiveness of our proposed controllers.
- Centroidal Voronoi tessellations (CVTs),
- diffusion processes,
- mobile actuator-sensor networks (MAS-Net),
- PI control

FullText(HTML)

References(40)

References

[1]	E. V. Dogadkina, M. G. Dontsov, and V. I. Parfenyuk, “The effect of diffusion processes on surface smoothing upon chemical polishing of titanium,” Protection of Metals and Physical Chemistry of Surfaces, vol. 52, no. 5, pp. 947–953, Sep. 2016.
[2]	S. O. Akintunde and P. A. Selyshchev, “The influence of radiationinduced vacancy on the formation of thin-film of compound layer during a reactive diffusion process,” J. Physics and Chemistry of Solids, vol. 92, pp. 64–69, May 2016.
[3]	M. Caputo and C. Cametti, “Fractional derivatives in the diffusion process in heterogeneous systems: the case of transdermal patches,” Mathematical Biosciences, vol. 291, pp. 38–45, Sep. 2017. doi: 10.1016/j.mbs.2017.07.004
[4]	P. Stoneman, “The diffusion of innovations: some reflections,” Int. J. Economics of Business, vol. 25, no. 1, pp. 85–95, Feb. 2018. doi: 10.1080/13571516.2017.1390834
[5]	D. Vališ, O. Nováček, K. Hasilováa, and J. Leuchter, “Modelling of degradation and a soft failure moment during the operation of a supercapacitor applying selected diffusion processes,” Engineering Failure Analysis, vol. 82, pp. 566–582, Dec. 2017. doi: 10.1016/j.engfailanal.2017.04.019
[6]	Y. Q. Chen, Z. M. Wang, and J. S. Liang, “Actuation scheduling in mobile actuator networks for spatial-temporal feedback control of a diffusion process with dynamic obstacle avoidance,” in Proc. IEEE Int. Conf. Mechatronics and Autom., vol. 2, pp. 752–757, Jul. 2005.
[7]	F. D. Ge, Y. Q. Chen, and C. H. Kou, “Cyber-physical systems as general distributed parameter systems: three types of fractional order models and emerging research opportunities,” IEEE/CAA J. Autom. Sinica, vol. 2, no. 4, pp. 353–357, Oct. 2015. doi: 10.1109/JAS.2015.7296529
[8]	M. J. Balas and S. A. Frost, “Robust adaptive model tracking for distributed parameter control of linear infinite-dimensional systems in Hilbert space,” IEEE/CAA J. Autom. Sinica, vol. 1, no. 3, pp. 294–301, Jul. 2014. doi: 10.1109/JAS.2014.7004687
[9]	Q. Du, V. Faber, and M. Gunzburger, “Centroidal voronoi tessellations: applications and algorithms,” SIAM Review, vol. 41, no. 4, pp. 637–676, Dec. 1999. doi: 10.1137/S0036144599352836
[10]	L. L. Ju, Q. Du, and M. Gunzburger, “Probabilistic methods for centroidal voronoi tessellations and their parallel implementations,” Parallel Computing, vol. 28, no. 10, pp. 1477–1500, Oct. 2002. doi: 10.1016/S0167-8191(02)00151-5
[11]	J. Cortés, S. Martínez, T. Karatas, and F. Bullo, “Coverage control for mobile sensing networks,” IEEE Trans. Robotics and Autom., vol. 20, no. 2, pp. 243–255, Apr. 2004. doi: 10.1109/TRA.2004.824698
[12]	Y. Q. Chen, K. L. Moore, and Z. Song, “Diffusion boundary determination and zone control via mobile actuator-sensor networks (MASnet): challenges and opportunities,” in Proc. SPIE Conf. Intelligent Computing: Theory and Applications II, vol. 5421, pp. 102–113, Apr. 2004.
[13]	Q. Du, M. Gunzburger, and L. L. Ju, “Advances in studies and applications of centroidal voronoi tessellations,” Numerical Mathematics:Theory,Methods and Applications, vol. 3, no. 2, pp. 119–142, May 2010. doi: 10.4208/nmtma
[14]	M. Santos, Y. Diaz-Mercado, and M. Egerstedt, “Coverage control for multirobot teams with heterogeneous sensing capabilities,” IEEE Robotics and Autom. Letters, vol. 3, no. 2, pp. 919–925, Apr. 2018.
[15]	S. Cheng and F. Yuan, “Coverage control for mobile sensor networks with limited communication ranges on a circle,” Automatica, vol. 92, pp. 155–161, Jun. 2018. doi: 10.1016/j.automatica.2018.03.014
[16]	M. Schwager, M. P. Vitus, S. Powers, D. Rus, and C. J. Tomlin, “Robust adaptive coverage control for robotic sensor networks,” IEEE Trans. Control Network Systems, vol. 4, no. 3, pp. 462–476, Sep. 2017. doi: 10.1109/TCNS.2015.2512326
[17]	J. Habibi, H. Mahboubi, and A. G. Aghdam, “Distributed coverage control of mobile sensor networks subject to measurement error,” IEEE Trans. Autom. Control, vol. 61, no. 11, pp. 3330–3343, Nov. 2016. doi: 10.1109/TAC.2016.2521370
[18]	A. L. Faulds and B. B. King, “Sensor location in feedback control of partial differential equation systems,” in Proc. IEEE Int. Conf. on Control Applications, pp. 536–541, Sep. 2000.
[19]	Y. Q. Chen, Z. M. Wang, and J. S. Liang, “Optimal dynamic actuator location in distributed feedback control of a diffusion process,” in Proc. 44th IEEE Conf. Decision and Control, and the European Control Conf., pp. 5562–5567, Dec. 2005.
[20]	D. Uciński, Optimal Measurement Methods for Distributed Parameter System Identification. Boca Raton: CRC Press, 2004.
[21]	H. Y. Chao and Y. Q. Chen, Remote Sensing and Actuation Using Unmanned Vehicles. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012.
[22]	Q. Y. Chen, Z. M. Wang, and K. L. Moore, “Optimal spraying control of a diffusion process using mobile actuator networks with fractional potential field based dynamic obstacle avoidance,” in Proc. IEEE Int. Conf. Networking, Sensing and Control (ICNSC), pp. 107–112, Apr. 2006.
[23]	H. Y. Chao, Y. Q. Chen, and W. Ren, “A study of grouping effect on mobile actuator sensor networks for distributed feedback control of diffusion process using central Voronoi tessellations,” in Proc. IEEE Int. Conf. Mechatronics and Automation, pp. 769–774, Jun. 2006.
[24]	H. Y. Chao, Y. Q. Chen, and W. Ren, “Consensus of information in distributed control of a diffusion process using centroidal voronoi tessellations,” in Proc. IEEE Conf. Decision and Control, pp. 1441–1446, Dec. 2007.
[25]	Y. Liu, F. Guo, X. Y. He, and Q. Hui, “Boundary control for an axially moving system with input restriction based on disturbance observers,” IEEE Trans. Systems,Man,and Cybernetics Systems, vol. 49, no. 11, pp. 2242–2253, Nov. 2019.
[26]	Y. Liu, Z. J. Zhao, and W. He, “Boundary control of an axially moving accelerated/decelerated belt system,” Int. J. Robust and Nonlinear Control, vol. 26, pp. 3849–3866, Mar. 2016.
[27]	Y. Liu, Z. J. Zhao, and W. He, “Stabilization of an axially moving accelerated/decelerated system via an adaptive boundary control,” ISA Trans., vol. 64, pp. 394–404, Sep. 2016. doi: 10.1016/j.isatra.2016.04.006
[28]	F. D. Ge, J. Chen, Y. Q. Chen, and C. H. Kou, “Optimal spraying control of a tempered time fractional order anomalous diffusion system,” in Proc. Int. Symposium on Fractional Signals and Systems, pp. 43–48, Oct. 2015.
[29]	J. Chen, B. Zhuang, Y. Q. Chen, and B. T. Cui, “Diffusion control for a tempered anomalous diffusion system using fractional-order PI controllers,” ISA Trans., vol. 82, pp. 94–106, Nov. 2018.
[30]	D. G. Luenberger and Y. Y. Ye, Linear and Nonlinear Programming, 3rd ed. Boston: Springer, 2008.
[31]	D. P. Bertsekas, Constrained Optimization and Lagrange Multiplier Methods. New York: Academic Press, 1982.
[32]	A. Howard, M. J. Matarić, and G. S. Sukhatme, “Mobile sensor network deployment using potential fields: a distributed, scalable solution to the area coverage problem,” in Proc. 6th Int. Symposium on Distributed Autonomous Robotic Systems (DARS02), vol. 5, pp. 299–308, Jun. 2002.
[33]	N. Heo and P. K. Varshney, “Energy-efficient deployment of intelligent mobile sensor networks,” IEEE Trans. Systems,Man,and Cybernetics–Part A:Systems and Humans, vol. 35, no. 1, pp. 78–92, Jan. 2005. doi: 10.1109/TSMCA.2004.838486
[34]	A. van der Schaft. L₂-gain and Passivity Techniques in Nonlinear Control, 2nd ed. New York: Springer-Verlag, 1999.
[35]	J. P. Lasalle, “Complete stability of a nonlinear control system,” in Proc. National Academy of Sciences of the United States of America, vol. 48, no. 4, pp. 600–603, Apr. 1962.
[36]	J. Cortés, S. Martínez, T. Karatas, and F. Bullo, “Coverage control for mobile sensing networks: variations on a theme,” in Proc. 10th Mediterranean Conf. Control and Automation-MED, Jul. 2002.
[37]	J. S. Liang and Y. Q. Chen, “Diff-MAS2D (version 0.9) user’s manual: a simulation platform for controlling distributed parameter systems (diffusion) with networked movable actuators and sensors (MAS) in 2D domain,” Techical Report, Center for Self-Organizing and Intelligent Systems (CSOIS), Department of Electrical and Computer Engineering, College of Engineering, Utah State University, USA, 2004.
[38]	J. S. Liang and Y. Q. Chen, “Diff/Wave-MAS2D: a simulation platform for measurement and actuation scheduling in distributed parameter systems with mobile actuators and sensors,” in Proc. IEEE Int. Conf. Mechatronics and Autom., pp. 2228–2233, Jul. 2005.
[39]	J. X. Cao, Y. Q. Chen, and C. P. Li, “Multi-UAV-based optimal cropdusting of anomalously diffusing infestation of crops,” in Proc. American Control Conf., pp. 1278–1283, Jul. 2015.
[40]	D. Y. Xue and Y. Q. Chen, System Simulation Techniques with MATLAB and Simulink. New Jersey, USA: Wiley & Sons, 2013.

Supplements(0)

Cited By

Proportional views

Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Figures(7)

Get Citation

PDF

XML

Article Metrics

Article views (1366) PDF downloads(50)

Highlights

Constructing a cyber-physical system framework based on centroidal Voronoi tessellations (CVTs).
Analyzing the convergence of the actuators location.
Developing a novel proportional integral (PI) control method for actuator motion planning.
Deriving optimal spraying control of a diffusion process with moving or static pollution sources.

An Improved Cooperative Team Spraying Control of a Diffusion Process With a Moving or Static Pollution Source

doi: 10.1109/JAS.2019.1911519

Abstract

References

Proportional views

Catalog

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Highlights

Export File

Citation

Format

Content