We consider a setup where a distributed set of sensors working cooperatively can estimate an unknown signal of interest, whereas any individual sensor cannot fulfil the task due to lack of necessary information diversity. This paper deals with these kinds of estimation and tracking problems and focuses on a class of simultaneous perturbation stochastic approximation (SPSA)-based consensus algorithms for the cases when the corrupted observations of sensors are transmitted between sensors with communication noise and the communication protocol has to satisfy a prespecified cost constraints on the network topology. Sufficient conditions are introduced to guarantee the stability of estimates obtained in this way, without resorting to commonly used but stringent conventional statistical assumptions about the observation noise such as randomness, independence, and zero mean. We derive an upper bound of the mean square error of the estimates in the problem of unknown time-varying parameters tracking under unknown but bounded observation errors and noisy communication channels. The result is illustrated by a practical application to the multi-sensor multi-target tracking problem.

We consider a dynamic network system of multiple heterogeneous sensors collaborating among themselves to estimate an unknown signal of interest. That communication capability is essential because individual senors cannot fulfill the task due to the lack of necessary information. This paper considers the distributed estimation or tracking problem and focuses on combining two algorithms: Simultaneous Perturbation Stochastic Approximation (SPSA) and consensus Local Voting Protocol (LVP). The new distributed algorithm is proposed for network systems under wide range of uncertainties including unknown-but-bounded drift of parameters and noise in observations. The suggested approach is illustrated by an application of the proposed algorithm to the solving the multisensor-multitarget problem.

This paper proposes a novel method for the unbounded oscillation prevention of an aircraft wing under the flexural torsional flutter, an innovative multiagent attitude to control an aircraft wing with a surface consisting of managed rotating “feathers” (agents). Theoretical evaluation of the method demonstrates its high aptitude to avoid an aircraft wing’s flexural-torsional vibrations via expansion of the model’s ability to dampen the wing oscillations. It potentially allows increasing an aircraft’s speed without misgiving of the flutter. A new way to control an aircraft wing based on the Speed-Gradient methodology is suggested to increase the maximal possible flight speed without a flutter occurrence. Provided experiments demonstrate the theoretical advantage of the multiagent approach to the “feathers” rotation control.