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Technological advancements in synthesizing devices at the nanoscale has produced a variety of analogues to classical systems elements, such as sensors, actuators, and control systems. We review recent experimental literature on nanoscale devices that have been produced to have useful systems functionality, as well as efforts to employ these devices in identification, estimation, and control. The integration...
Synchronization of networks composed by fully-actuated Lagrangian systems has received a lot of attention from the control theory community. Unfortunately, the case of networks composed by under-actuated systems of the same kind has not been deeply studied and the related literature is very reduced. The aim of this paper is to contribute towards the establishment of a control scheme for this class...
We have recently proposed a “surplus-based” algorithm which solves the multi-agent average consensus problem on general strongly connected and static digraphs. The essence of that algorithm is to employ an additional variable to keep track of the state changes of each agent, thereby achieving averaging even though the state sum is not preserved. In this paper, we extend this approach to the more challenging...
This paper addresses semistable stochastic Linear-Quadratic Consensus (LQC) problems motivated by the recently developed Optimal Semistable Control (OSC) and semistable H2 control problems. OSC deals with linear-quadratic optimal semistabilization. In the framework of OSC, the closed-loop system is not asymptotically stable, but semistable. Semistability is the property that every trajectory of the...
This paper studies finite-time consensus for networked multi-agent systems with second-order dynamics in the presence of unknown inherent nonlinear dynamics under an undirected switching interaction graph. In particular, all agents are assumed to share a common sensing range. More precisely, each agent can only communicate with other agents who are within the sensing range of itself. We propose a...
In several multi agent control problems, the convergence properties and speed of the system depend on the algebraic connectivity of the graph. We discuss a particular event-triggered consensus scenario, and show that the availability of an estimate of the algebraic connectivity could be used for adapting the behavior of the average consensus algorithm. We present a novel distributed algorithm for...
The paper introduces a new class of consensus protocols to reach the agreement in networks of agents with a discrete time dynamics. In order to guarantee the convergence of the proposed algorithms, some general results are proved in the framework of non negative matrix theory. In addition, numerous numerical experiments show that the proposed iterative schemes enjoy good rate of convergence even in...
Uncertainties are ubiquitous in mathematical models of complex systems and this paper considers the incorporation of generalized polynomial chaos expansions for uncertainty propagation and quantification into robust control design. Generalized polynomial chaos expansions are more computationally efficient than Monte Carlo simulation for quantifying the influence of stochastic parametric uncertainties...
This paper investigates a decentralized H2 state feedback control for multi-channel linear time-invariant stochastic systems governed by Itoô's differential equation. After establishing the necessary condition based on stochastic algebraic Riccati equation (SARE) for the existence of the strategy set, it is shown that the same conditions can be written by the linear matrix inequality (LMI). The equivalence...
A previous paper (Spall, 2010) described a method for estimating the reliability of a complex system based on a combination of full system and subsystem tests. A maximum likelihood estimate (MLE) is formed to estimate the subsystem reliabilities and the full system reliability. While the previous paper gave conditions under which the MLE converges to the true reliability as the sample size gets large,...
In this paper, we study the problem of stabilization of nonlinear system in Lure form with uncertainty at the input and output channels. The channel uncertainty is modeled using Bernoulli random variable. Generalization of Positive Real Lemma for stochastic systems are derived to prove the main result of this paper providing sufficient condition for the mean square exponential stability of the closed...
The main problem of stochastic nonlinear model predictive control (SNMPC) is that the equations for state prediction and calculation of the expected reward are in general not solvable in closed form. A popular approach is to approximate the occurring continuous probability density functions by a discrete density representation, which allows an analytical solution of the SNMPC equations. In this paper,...
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