Coverage-optimization based guidance of mobile agents for improved control of distributed parameter systems
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摘要
The control problem of a class of parabolic distributed parameter systems(DPSs) is investigated by using mobile agents with capabilities of sensing and actuating. The guidance strategies of mobile agents based on coverage optimization methods are proposed to improve the control performance of the system and make the state norm of the system converge to zero faster. The coverage optimization problems are constructed based on the measurement of each agent. By solving the coverage optimization problems, the local optimal moving direction of each agent can be obtained. Then the gradient-based agent motion control laws are established. With the indicator function and the surface delta function, this method is generalized to n-dimensional space, and suitable for any sensing region with piecewise smooth boundaries. The stability and control performance of the system are analyzed. Numerical simulations show the effectiveness of the proposed methods.
The control problem of a class of parabolic distributed parameter systems(DPSs) is investigated by using mobile agents with capabilities of sensing and actuating. The guidance strategies of mobile agents based on coverage optimization methods are proposed to improve the control performance of the system and make the state norm of the system converge to zero faster. The coverage optimization problems are constructed based on the measurement of each agent. By solving the coverage optimization problems, the local optimal moving direction of each agent can be obtained. Then the gradient-based agent motion control laws are established. With the indicator function and the surface delta function, this method is generalized to n-dimensional space, and suitable for any sensing region with piecewise smooth boundaries. The stability and control performance of the system are analyzed. Numerical simulations show the effectiveness of the proposed methods.
The control problem of a class of parabolic distributed parameter systems(DPSs) is investigated by using mobile agents with capabilities of sensing and actuating. The guidance strategies of mobile agents based on coverage optimization methods are proposed to improve the control performance of the system and make the state norm of the system converge to zero faster. The coverage optimization problems are constructed based on the measurement of each agent. By solving the coverage optimization problems, the local optimal moving direction of each agent can be obtained. Then the gradient-based agent motion control laws are established. With the indicator function and the surface delta function, this method is generalized to n-dimensional space, and suitable for any sensing region with piecewise smooth boundaries. The stability and control performance of the system are analyzed. Numerical simulations show the effectiveness of the proposed methods.
引文
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[15]CHAO H Y,CHEN Y Q,REN W.A study of grouping effect on mobile actuator sensor networks for distributed feedback control of diffusion process using central Voronoi tessellations.Proc.of the IEEE International Conference on Mechatronics and Automation,2006:769-774.
[16]CHAO H Y,CHEN Y Q,REN W.Consensus of information in distributed control of a diffusion process using centroidal Voronoi tessellations.Proc.of the 46th IEEE Conference on Decision and Control,2007:1141-1146.
[17]CAO J X,CHEN Y Q,LI C P.Multi-UAV-based optimal cropdusting of anomalously diffusing infestation of crops.Proc.of American Control Conference,2015:1278-1283.
[18]CHEN J,ZHUANG B,CHEN Y Q,et al.Diffusion control for a tempered anomalous diffusion system using fractional-order PI controllers.ISA Transactions,2018,82:94-106.
[19]DEMETRIOU M A.Adaptive control of 2-D PDEs using mobile collocated actuator/sensor pairs with augmented vehicle dynamics.IEEE Trans.on Automatic Control,2012,57(12):2979-2993.
[20]DEMETRIOU M A,GATSONIS N,COURT J R.Lyapunov based guidance of a mobile sensing agent for state estimation of a gaseous source in a 3D spatial domain.Proc.of the 50th IEEE Conference on Decision and Control and European Control Conference,2011:1986-1992.
[21]DEMETRIOU M A,EGOROVA T,GATSONIS N A.Estimation of a gaseous release into the atmosphere using a formation of UAVs.IFAC-Papers On Line,2016,49(18):110-115.
[22]MU W Y,CUI B T,LI W,et al.Improving control and estimation for distributed parameter systems utilizing mobile actuator-sensor network.ISA Transactions,2014,53(4):1087-1095.
[23]JIANG Z X,CUI B T,LOU X Y,et al.Improved control of distributed parameter systems using wireless sensor and actuator networks:an observer-based method.Chinese Physics B,2017,26(4):040201.
[24]HABIBI J,MAHBOUBI H,AGHDAM A G.A gradient-based coverage optimization strategy for mobile sensor networks.IEEE Trans.on Control of Network Systems,2017,4(3):477-488.
[25]CONLON L.Differentiable manifolds.Boston:Birkha User,2008.
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[28]SALSA S.Partial differential equations in action:from modelling to theory.New York:Springer,2015.
[29]PAZY A.Semigroups of linear operators and applications to partial differential equations.Applied Mathematical Sciences,1983.
[30]LANGE R J.Potential theory,path integrals and the Laplacian of the indicator.Journal of High Energy Physics,2012,2012(11):32.
[31]LASALLE J P.Stability theory for ordinary differential equations.Journal of Differential Equations,1968,4(1):57-65.
[32]SLEMROD M.Asymptotic behavior of a class of abstract dynamical systems.Journal of Differential Equations,1970,7(3):584-600.
[33]ALNAS M S,BLECHTA J,HAKE J,et al.The FEniCS project version 1.5.Archive of Numerical Software,2015,3(100):9-23.
[2]BUTKOVSKII A G,PUSTYL’NIKOV A M.Mobile control of distributed parameter systems.New York:Halsted Press,1987.
[3]JAI A E,PRITCHARD A J.Sensors and controls in the analysis of distributed systems.England:Halsted Press,1988.
[4]KHAPALOV A Y.Continuous observability for parabolic system under observations of discrete type.IEEE Trans.on Automatic Control,1993,38(9):1388-1391.
[5]UCI’NSKI D.Optimal measurement methods for distributed parameter system identification.New York:CRC Press,2005.
[6]AKYILDIZ I F,KASIMOGLU I H.Wireless sensor and actor networks:research challenges.Ad Hoc Networks,2004,2(4):351-367.
[7]CHEN Y Q,WANG Z M,LIANG J S.Optimal dynamic actuator location in distributed feedback control of a diffusion process.Proc.of the 44th IEEE Conference on Decision and Control,2005:5662-5667.
[8]DEMETRIOU M A.Guidance of mobile actuator-plus-sensor networks for improved control and estimation of distributed parameter systems.IEEE Trans.on Automatic Control,2010,55(7):1570-1584.
[9]BAO L P,FEI S,CHAI L.Control synthesis of linear distributed parameter switched systems.Journal of Systems Engineering and Electronics,2015,26(3):565-572.
[10]TRICAUD C,CHEN Y Q.Optimal mobile sensing and actuation policies in cyber-physical systems.London:Springer,2012.
[11]CHEN Y Q,MOORE K L,SONG Z.Diffusion boundary determination and zone control via mobile actuator-sensor networks(MAS-net):challenges and opportunities.Proc.of the SPIE:Intelligent Computing:Theory and Applications,2004,5421:102-113.
[12]MOORE K L,CHEN Y Q,SONG Z.Diffusion-based path planning in mobile actuator-sensor networks(MAS-net):some preliminary results.Proc.of the SPIE:Intelligent Computing:Theory and Applications,2004,5421:58-69.
[13]CORTES J,MARTINEZ S,KARATAS T,et al.Coverage control for mobile sensing networks.IEEE Trans.on Robotics and Automation,2004,20(2):243-255.
[14]CHEN Y Q,WANG Z M,LIANG J S.Optimal dynamic actuator location in distributed feedback control of a diffusion process.International Journal of Sensor Networks,2007,2(3/4):169-178.
[15]CHAO H Y,CHEN Y Q,REN W.A study of grouping effect on mobile actuator sensor networks for distributed feedback control of diffusion process using central Voronoi tessellations.Proc.of the IEEE International Conference on Mechatronics and Automation,2006:769-774.
[16]CHAO H Y,CHEN Y Q,REN W.Consensus of information in distributed control of a diffusion process using centroidal Voronoi tessellations.Proc.of the 46th IEEE Conference on Decision and Control,2007:1141-1146.
[17]CAO J X,CHEN Y Q,LI C P.Multi-UAV-based optimal cropdusting of anomalously diffusing infestation of crops.Proc.of American Control Conference,2015:1278-1283.
[18]CHEN J,ZHUANG B,CHEN Y Q,et al.Diffusion control for a tempered anomalous diffusion system using fractional-order PI controllers.ISA Transactions,2018,82:94-106.
[19]DEMETRIOU M A.Adaptive control of 2-D PDEs using mobile collocated actuator/sensor pairs with augmented vehicle dynamics.IEEE Trans.on Automatic Control,2012,57(12):2979-2993.
[20]DEMETRIOU M A,GATSONIS N,COURT J R.Lyapunov based guidance of a mobile sensing agent for state estimation of a gaseous source in a 3D spatial domain.Proc.of the 50th IEEE Conference on Decision and Control and European Control Conference,2011:1986-1992.
[21]DEMETRIOU M A,EGOROVA T,GATSONIS N A.Estimation of a gaseous release into the atmosphere using a formation of UAVs.IFAC-Papers On Line,2016,49(18):110-115.
[22]MU W Y,CUI B T,LI W,et al.Improving control and estimation for distributed parameter systems utilizing mobile actuator-sensor network.ISA Transactions,2014,53(4):1087-1095.
[23]JIANG Z X,CUI B T,LOU X Y,et al.Improved control of distributed parameter systems using wireless sensor and actuator networks:an observer-based method.Chinese Physics B,2017,26(4):040201.
[24]HABIBI J,MAHBOUBI H,AGHDAM A G.A gradient-based coverage optimization strategy for mobile sensor networks.IEEE Trans.on Control of Network Systems,2017,4(3):477-488.
[25]CONLON L.Differentiable manifolds.Boston:Birkha User,2008.
[26]CURTAIN R F,ZWART H.An introduction to infinitedimensional linear systems theory.New York:SpringerVerlag,1995.
[27]SHOWALTER R E.Hilbert space methods in partial differential equations.London:Pitman,1979.
[28]SALSA S.Partial differential equations in action:from modelling to theory.New York:Springer,2015.
[29]PAZY A.Semigroups of linear operators and applications to partial differential equations.Applied Mathematical Sciences,1983.
[30]LANGE R J.Potential theory,path integrals and the Laplacian of the indicator.Journal of High Energy Physics,2012,2012(11):32.
[31]LASALLE J P.Stability theory for ordinary differential equations.Journal of Differential Equations,1968,4(1):57-65.
[32]SLEMROD M.Asymptotic behavior of a class of abstract dynamical systems.Journal of Differential Equations,1970,7(3):584-600.
[33]ALNAS M S,BLECHTA J,HAKE J,et al.The FEniCS project version 1.5.Archive of Numerical Software,2015,3(100):9-23.