Optimal switching policy for performance enhancement of distributed parameter systems based on event-driven control

This paper aims to improve the performance of a class of distributed parameter systems for the optimal switching of actuators and controllers based on event-driven control. It is assumed that in the available multiple actuators, only one actuator can receive the control signal and be activated over an unfixed time interval, and the other actuators keep dormant. After incorporating a state observer into the event generator, the event-driven control loop and the minimum inter-event time are ultimately bounded. Based on the event-driven state feedback control, the time intervals of unfixed length can be obtained. The optimal switching policy is based on finite horizon linear quadratic optimal control at the beginning of each time subinterval. A simulation example demonstrate the effectiveness of the proposed policy.

[1]  Jan Lunze,et al.  A state-feedback approach to event-based control , 2010, Autom..

[2]  Sun Feng-lan,et al.  Finite-time consensus for leader-following multi-agent systems over switching network topologies , 2013 .

[3]  Michael A. Demetriou,et al.  A new integrated output feedback controller synthesis and collocated actuator/sensor scheduling framework for distributed parameter processes , 2005, Comput. Chem. Eng..

[4]  Michael A. Demetriou,et al.  Actuator and controller scheduling in nonlinear transport-reaction processes , 2008 .

[5]  Xiaofeng Wang,et al.  Event-Triggering in Distributed Networked Control Systems , 2011, IEEE Transactions on Automatic Control.

[6]  Michael A. Demetriou Design of consensus and adaptive consensus filters for distributed parameter systems , 2010, Autom..

[7]  Lian-He Li Elliptic holes in octagonal quasicrystals , 2013 .

[8]  Michael A. Demetriou,et al.  Guidance of Mobile Actuator-Plus-Sensor Networks for Improved Control and Estimation of Distributed Parameter Systems , 2010, IEEE Transactions on Automatic Control.

[9]  Feng Tan,et al.  Relations between Mass Change and Frequency Shift of a QCM Sensor in Contact with Viscoelastic Medium , 2013 .

[10]  Michael A. Demetriou,et al.  A new actuator activation policy for performance enhancement of controlled diffusion processes , 2004, Autom..

[11]  Alberto Bemporad,et al.  Event-driven optimization-based control of hybrid systems with integral continuous-time dynamics , 2009, Autom..

[12]  Paulo Tabuada,et al.  Event-Triggered Real-Time Scheduling of Stabilizing Control Tasks , 2007, IEEE Transactions on Automatic Control.

[13]  Y. Tu,et al.  A population-level model from the microscopic dynamics in Escherichia coli chemotaxis via Langevin approximation , 2012 .

[14]  A. Armaou,et al.  Optimal actuator/sensor placement for linear parabolic PDEs using spatial H2 norm , 2006 .

[15]  Athanasios V. Vasilakos,et al.  Immunizations on small worlds of tree-based wireless sensor networks , 2012 .

[16]  Hiroki Tanabe,et al.  Equations of evolution , 1979 .

[17]  Zhang Chun,et al.  A target group tracking algorithm for wireless sensor networks using azimuthal angle of arrival information , 2012 .

[18]  Orest V. Iftime,et al.  Optimal control of switched distributed parameter systems with spatially scheduled actuators , 2009, Autom..