Controlling Diffusive Network Processes Using Incidental Measurements and Actuation

Feedback control of diffusive network dynamics using incidental measurements and actuation is explored. A standard model for diffusion or synchronization in networks is enhanced to represent two incidental control architectures: one in which clocked measurements from a stochastically-moving platform are used to regulate a fixed actuator, and a second where the sensor and actuator are collocated on a moving platform. Simple proportional-integral-derivative control schemes are studied. For both control architectures, low-gain controllers are shown to achieve regulation in a mean-square sense. A simulation example is presented, which demonstrates that the incidental control architectures allow for practical regulation, and in fact, can sometimes outperform a fixed control architecture.