Abstract:
We consider performance deterioration of interconnected linear dynamical networks subject to exogenous stochastic disturbances. The focus of this paper is on first-order and second-order linear consensus networks. We employ the expected value of the steady state dispersion of the state of the entire network as a performance measure and develop a graph-theoretic methodology to relate structural specifications of the underlying graphs of the network to the performance measure. We explicitly quantify several inherent fundamental limits on the best achievable levels of performance in linear consensus networks and show that these limits of performance are merely imposed by the specific structure of the underlying graphs. Furthermore, we discover new connections between notions of sparsity and the performance measure. Particularly, we characterize several fundamental tradeoffs that reveal interplay between the performance measure and various sparsity measures of a linear consensus network. At the end, we apply our results to two real-world dynamical networks and provide energy interpretations for the proposed performance measures. It is shown that the total power loss in synchronous power networks and total kinetic energy of a network of autonomous vehicles in a formation are viable performance measure for these networks and fundamental limits on these measures quantify the best achievable levels of energy-efficiency in these dynamical networks.

Abstract:
In this paper, we develop a novel unified methodology for performance and robustness analysis of linear dynamical networks. We introduce the notion of systemic measures for the class of first--order linear consensus networks. We classify two important types of performance and robustness measures according to their functional properties: convex systemic measures and Schur--convex systemic measures. It is shown that a viable systemic measure should satisfy several fundamental properties such as homogeneity, monotonicity, convexity, and orthogonal invariance. In order to support our proposed unified framework, we verify functional properties of several existing performance and robustness measures from the literature and show that they all belong to the class of systemic measures. Moreover, we introduce new classes of systemic measures based on (a version of) the well--known Riemann zeta function, input--output system norms, and etc. Then, it is shown that for a given linear dynamical network one can take several different strategies to optimize a given performance and robustness systemic measure via convex optimization. Finally, we characterized an interesting fundamental limit on the best achievable value of a given systemic measure after adding some certain number of new weighted edges to the underlying graph of the network.

Abstract:
Our goal is to analyze performance of stable linear dynamical networks subject to external stochastic disturbances. The square of the $\mathcal H_2$-norm of the network is used as a performance measure to quantify the expected steady-state dispersion of the outputs of the network. We show that this performance measure can be tightly bounded from below and above by some spectral functions of the state-space matrices of the network. This result is applied to a class of cyclic linear networks and shown that their performance measure scale quadratically with the network size.

Abstract:
We consider the class of spatially decaying systems, where the underlying dynamics are spatially decaying and the sensing and controls are spatially distributed. This class of systems arise in various applications where there is a notion of spatial distance with respect to which couplings between the subsystems can be quantified using a class of coupling weight functions. We exploit spatial decay property of the underlying dynamics of the system to introduce a class of sparsity and spatial localization measures for spatially distributed systems. We develop a new methodology based on concepts of $q$-Banach algebras of spatially decaying operators that enable us to establish a relationship between spatial decay properties of spatially decaying systems and their sparsity and spatial localization features. Moreover, it is shown that the inverse-closedness property of operator algebras plays a central role in exploiting various structural properties of spatially decaying systems. We characterize conditions for exponentially stability of spatially decaying system over $q$-Banach algebras and prove that the unique solutions of the Lyapunov and Riccati equations over a proper $q$-Banach algebra also belong to the same $q$-Banach algebra. It is shown that the quadratically optimal state feedback controllers for spatially decaying systems are sparse and spatially localized in the sense that they have near-optimal sparse information structures.

Abstract:
We consider the problem of optimal sparse output feedback controller synthesis for continuous linear time invariant systems when the feedback gain is static and subject to specified structural constraints. Introducing an additional term penalizing the number of non-zero entries of the feedback gain into the optimization cost function, we show that this inherently non-convex problem can be equivalently cast as a rank constrained optimization, hence, it is an NP-hard problem. We further exploit our rank constrained approach to define a structured output feedback control feasibility test with global convergence property, then, obtain upper/lower bounds for the optimal cost of the sparse output feedback control problem. Moreover, we show that our problem reformulation allows us to incorporate additional implementation constraints, such as norm bounds on the control inputs or system output, by assimilating them into the rank constraint. We propose to utilize a version of the Alternating Direction Method of Multipliers (ADMM) as an efficient method to sub-optimally solve the equivalent rank constrained problem. As a special case, we study the problem of designing the sparsest stabilizing output feedback controller, and show that it is, in fact, a structured matrix recovery problem where the matrix of interest is simultaneously sparse and low rank. Furthermore, we show that this matrix recovery problem can be equivalently cast in the form of a canonical and well-studied rank minimization problem. We finally illustrate performance of our proposed methodology using numerical examples.

Abstract:
We provide an analysis of the classic Kuramoto model of coupled nonlinear oscillators that goes beyond the existing results for all-to-all networks of identical oscillators. Our work is applicable to oscillator networks of arbitrary interconnection topology with uncertain natural frequencies. Using tools from spectral graph theory and control theory, we prove that for couplings above a critical value, the synchronized state is locally asymptotically stable, resulting in convergence of all phase differences to a constant value, both in the case of identical natural frequencies as well as uncertain ones. We further explain the behavior of the system as the number of oscillators grows to infinity.

Abstract:
We consider a network of evolving opinions. It includes multiple individuals with first-order opinion dynamics defined in continuous time and evolving based on a general exogenously defined time-varying underlying graph. In such a network, for an arbitrary fixed initial time, a subset of individuals forms an eminence grise coalition, abbreviated as EGC, if the individuals in that subset are capable of leading the entire network to agreeing on any desired opinion, through a cooperative choice of their own initial opinions. In this endeavor, the coalition members are assumed to have access to full profile of the underlying graph of the network as well as the initial opinions of all other individuals. While the complete coalition of individuals always qualifies as an EGC, we establish the existence of a minimum size EGC for an arbitrary time-varying network; also, we develop a non-trivial set of upper and lower bounds on that size. As a result, we show that, even when the underlying graph does not guarantee convergence to a global or multiple consensus, a generally restricted coalition of agents can steer public opinion towards a desired global consensus without affecting any of the predefined graph interactions, provided they can cooperatively adjust their own initial opinions. Geometric insights into the structure of EGC's are given. The results are also extended to the discrete time case where the relation with Decomposition-Separation Theorem is also made explicit.

Agriculture has historically played a central role in the
economy, life and culture of the Iranian population. Nowadays, this sector is facing
the reality that its natural fresh water resources become fully utilized. Considering
the climate conditions and limitation of using new water resources andthe necessity
of increasing agricultural product as a result of population growth, there is
a general doubt about Iran’s ability to maintain this level of production amid the
mounting water challenges, among other obstacles. Therefore, the evaluation of virtual
water and water footprint can provide new indicators for informing water policy
decisions. So, in
order to study the situation at the national level, we estimated
virtual water consumption in term of virtual water theory as well water footprint
in agriculture sector of Iran. Data from 2001-2008 were used to account for yearly.
The results of this study show that Iran has water import dependency and also net
water import is 12.7 billion m^{3 }averages. So Iran country saved 12.7
billion m^{3} from their domestic water resource for utilization in other
sectors. Finally, it should be concluded that virtual water trade as a policy
measure to water resources management will be provided to a great extent in
order to reach both significant water saving and environmental sustainability.

Abstract:
The recent decades have seen the increase in demand for reliable and clean form of electricity derived from renewable energy sources. One such example is solar power. The challenge remains to maximize the capture of the rays from the sun for conversion into electricity. This paper presents fabrication and installation of a solar panel mount with a dual-axis solar tracking controller. This is done so that rays from the sun fall perpendicularly unto the solar panels to maximize the capture of the rays by pointing the solar panels towards the sun and following its path across the sky. Thus electricity and efficiency increased.

Abstract:
Applicationsof Electro-Rheological (ER)or Magneto-Rheological (MR) fluids as typical smart materials have been widely investigated over the past decades (since their
introduction in 40’s). The special applications of these materials as a means of noise suppression are not yet investigated. Constrained Layer Damping (CLD) sheets can be
realized by incorporating EMR (ER/MR) materials. In this way,a multilayered damping sheet is obtained with
adaptive (tunable) stiffness and damping characteristics. These
properties are easily changed in proportion to the electric (magnetic) field applied
upon the EMR layer.This notion has been introduced for semi-active
vibration control problems.Herein, such panels incorporating EMR material are proposed for adaptive acoustic treatments. Modeling (simulation) of a 3-layered panel with the middle layer being
EMR with adjustable