Electrical Engineering-Systems Dept.

*** SEMINAR ***

Netzer Bar Am

(M.Sc. student under the supervision of Prof. Emilia Fridman)

on the subject:

Network-based  Control/Filtering of a Class of Parabolic Systems

In many practical applications, measurements of the process outputs are available from the sensors at discrete times. A classical approach to sampled-data control is based on discretization, which looses information on the inter-sampling behavior and which becomes complicated in the presence of uncertainties/nonlinearities. To avoid the latter problem, a time-delay approach to sampled-data control was introduced, where the system was modeled as a continuous-time system with the delayed control input. Sampled-data control of linear time-invariant of distributed parameter systems has been studied via discretization (see Logemann et al., 2005). 

We develop, for the first time, sampled-data  control for a class of  semilinear diffusion systems. Network of N stationary sensing devices provides spatially averaged state measurements over the sampling spatial domains.

 Our sampled-data static output feedback enters the equations through N shape functions (which are localized in the space) multiplied by the corresponding state measurements. Sufficient conditions for the exponential stability and for

L2-gain analysis of the closed-loop system is derived via time-delay approach and direct Lyapunov method. Then the results are extended to network-based

 Filtering, where sensors and actuators exchange data via communication network and where variable sampling and communication delays are taken into account. Numerical examples of chemical reactors and of air-pollution systems illustrate the efficiency of the method. The results have potential applications to smart buildings.