<![CDATA[ IEEE Transactions on Automatic Control - new TOC ]]>
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TOC Alert for Publication# 9 2018March 19<![CDATA[Table of contents]]>633C1C442<![CDATA[IEEE Control Systems Society]]>633C2C2151<![CDATA[Scanning the Issue]]>63361761883<![CDATA[Covariance Intersection for Partially Correlated Random Vectors]]>633619629348<![CDATA[Safety Verification and Control for Collision Avoidance at Road Intersections]]>6336306421414<![CDATA[Stability Analysis of Monotone Systems via Max-Separable Lyapunov Functions]]>633643656392<![CDATA[Model Reduction of Networked Multiagent Systems by Cycle Removal]]>633657671716<![CDATA[Steering the Eigenvalues of the Density Operator in Hamiltonian-Controlled Quantum Lindblad Systems]]>$n$ -dimensional Lindblad control system can be separated into its inter- and intraorbit dynamics when there is fast controllability. This can be viewed as a control system on the simplex of density operator spectra, where projectors representing the eigenspaces are viewed as control variables. The local controllability properties of this control system can be analyzed when the control set of projectors is limited to a finite subset. In particular, there is a natural finite subset of $n!$ projector tuples that are effective for low-purity orbits.]]>6336726811216<![CDATA[An Exact Convex Formulation of the Optimal Power Flow in Radial Distribution Networks Including Transverse Components]]>ex ante for the exactness of the optimal solutions. The same formulations also have not correctly accounted for the lines’ ampacity constraint. Similar to the inclusion of upper voltage-magnitude limit, the SOCP relaxation faces difficulties when the ampacity constraints of the lines are binding. In order to overcome these limitations, we propose a convex formulation for the OPF in radial power grids, for which the ac-OPF equations, including the transverse parameters, are considered. To limit the lines’ current together with the nodal voltage-magnitudes, we augment the formulation with a new set of more conservative constraints. Sufficient conditions are provided to ensure the feasibility and optimality of the proposed OPF solution. Furthermore, the proofs of the exactness of the SOCP relaxation are provided. Using standard power grids, we show that these conditions are mild and hold for real distribution networks.]]>633682697658<![CDATA[Weakly Coupled Dynamic Program: Information and Lagrangian Relaxations]]>633698713443<![CDATA[Distributed Online Optimization in Dynamic Environments Using Mirror Descent]]>a priori. The gap between the two losses is defined as dynamic regret. We establish a regret bound that scales inversely in the spectral gap of the network and represents the deviation of minimizer sequence with respect to the given dynamics. We show that our framework subsumes a number of results in distributed optimization.]]>633714725772<![CDATA[Riccati Observers for the Nonstationary PnP Problem]]>static Perspective-n-Point problem addressed with iterative algorithms is that body motion is not only allowed but also used as a source of information that improves the estimation possibilities. With respect to the probabilistic framework commonly used in other studies that develop extended Kalman filter solutions, the deterministic approach here adopted is better suited to point out the observability conditions, that involve the number and disposition of the source points in combination with body motion characteristics, under which the proposed observers ensure robust estimation of the body pose. These observers are here named Riccati observers because of the instrumental role played by the continuous Riccati equation in the design of the observers and in the Lyapunov stability and convergence analysis that we develop independently of the well-known complementary (either deterministic or probabilistic) optimality properties associated with Kalman filtering. The set of these observers also encompasses extended Kalman filter solutions. Another contribution of this study is to show the importance of using body motion to improve the observers performance and, when this is possible, of measuring the body translational velocity in the inertial frame rather than in the body frame to allow for the body pose estimation from a single source point taken as the origin of the inertial frame. This latter possibility finds a natural extension-
in the Simultaneous Localisation And Mapping (SLAM) problem in Robotics.]]>6337267411069<![CDATA[Asynchronous Decision-Making Dynamics Under Best-Response Update Rule in Finite Heterogeneous Populations]]>633742751388<![CDATA[Scalable Design of Structured Controllers Using Chordal Decomposition]]>a priori structural constraints, which is a nonconvex problem in general. Previous work has focused on either characterizing special structures that result into convex formulations, or employing certain techniques to allow convex relaxations of the original problem. In this paper, by exploiting the underlying sparsity properties of the problem, and using chordal decomposition, we propose a scalable algorithm to obtain structured feedback gains to stabilize a large-scale system. We first extend the chordal decomposition theorem for positive semidefinite matrices to the case of matrices with block-chordal sparsity. Then, a block-diagonal Lyapunov matrix assumption is used to convert the design of structured feedback gains into a convex problem, which inherits the sparsity pattern of the original problem. Combining these two results, we propose a sequential design method to obtain structured feedback gains clique-by-clique over a clique tree of the block-chordal matrix, which only needs local information and helps ensure privacy of model data. Several illustrative examples demonstrate the efficiency and scalability of the proposed sequential design method.]]>633752767929<![CDATA[A Dynamic Game Model of Collective Choice in Multiagent Systems]]>a priori individual preference. Agents are assumed linear and coupled through a modified form of quadratic cost, whereby the terminal cost captures the discrete choice component of the problem. Following the mean field games methodology, we identify sufficient conditions under which allocations of destination choices over agents lead to self-replication of the overall mean trajectory under the best response by the agents. Importantly, we establish that when the number of agents increases sufficiently, 1) the best response strategies to the self-replicating mean trajectories qualify as epsilon-Nash equilibria of the population game; and 2) these epsilon-Nash strategies can be computed solely based on the knowledge of the joint probability distribution of the initial conditions, dynamics parameters, and destination preferences, now viewed as random variables. Our results are illustrated through numerical simulations.]]>633768782854<![CDATA[Cooperative Output Regulation for a Class of Nonlinear Multi-agent Systems with Unknown Control Directions subject to Switching Networks]]>633783790561<![CDATA[Pulse-Based Control Using Koopman Operator Under Parametric Uncertainty]]>633791796440<![CDATA[Multi-Sensor Kalman Filtering With Intermittent Measurements]]>633797804349<![CDATA[A Data-Driven Computation Method for the Gap Metric and the Optimal Stability Margin]]>633805810287<![CDATA[Composite Model Reference Adaptive Control with Parameter Convergence Under Finite Excitation]]>633811818825<![CDATA[Alternating Projections Methods for Discrete-Time Stabilization of Quantum States]]>633819826279<![CDATA[Complexity Certification of a Distributed Augmented Lagrangian Method]]>$epsilon$-optimal solution both in terms of suboptimality and infeasibility is $O(frac{1}{epsilon })$ iterations. Moreover, we provide a valid upper bound for the optimal dual multiplier, which enables us to explicitly specify these complexity bounds. We also show how to choose the step-size parameter to minimize the bounds on the convergence rates. Finally, we discuss a motivating example, a model predictive control problem, involving a finite number of subsystems, which interact with each other via a general network.]]>633827834294<![CDATA[Distributed Coordination of DERs With Storage for Dynamic Economic Dispatch]]>633835842461<![CDATA[Exponential Stability of Coupled Linear Delay Time-Varying Differential–Difference Equations]]>633843848257<![CDATA[Switching Control for Parameter Identifiability]]>633849856298<![CDATA[Stabilization of 2-D Switched Systems With All Modes Unstable via Switching Signal Regulation]]>633857863948<![CDATA[Distributed Control for Reaching Optimal Steady State in Network Systems: An Optimization Approach]]>6338648711086<![CDATA[Low-Rank Modifications of Riccati Factorizations for Model Predictive Control]]>MPC), the control input is computed by solving a constrained finite-time optimal control (CFTOC) problem at each sample in the control loop. The main computational effort when solving the CFTOC problem using an active-set (AS) method is often spent on computing the search directions, which in MPC corresponds to solving unconstrained finite-time optimal control (UFTOC) problems. This is commonly performed using Riccati recursions or generic sparsity exploiting algorithms. In this paper, the focus is efficient search direction computations for AS type methods. The system of equations to be solved at each AS iteration is changed only by a low-rank modification of the previous one, and exploiting this structured change is important for the performance of AS-type solvers. In this paper, theory for how to exploit these low-rank changes by modifying the Riccati factorization between AS iterations in a structured way is presented. A numerical evaluation of the proposed algorithm shows that the computation time can be significantly reduced by modifying, instead of re-computing, the Riccati factorization. This speedup can be important for AS-type solvers used for linear, nonlinear, and hybrid MPC.]]>633872879441<![CDATA[On the Design of Attitude Complementary Filters on $text{SO}(3)$]]>$text{SO}(3)$. We derive explicit time solutions of the attitude estimation error dynamics of the filters (in the disturbance-free case) and analyze their performance and robustness with respect to measurement disturbances. The stability and performance properties of the filters can be easily deduced from the obtained closed-form solutions. A new class of attitude complementary filters on $text{SO}(3)$ with state-dependent gains is proposed and shown to exhibit improved performance and robustness properties compared to the fixed-gain traditional complementary filter on $text{SO}(3)$.]]>633880887530<![CDATA[Convergent Fault Estimation for Linear Systems With Faults and Disturbances]]>633888893808<![CDATA[A Framework for Global Robust Output Regulation of Nonlinear Lower Triangular Systems With Uncertain Exosystems]]>633894901349<![CDATA[Discrete-Time Robust Hierarchical Linear-Quadratic Dynamic Games]]>633902909463<![CDATA[Corrections to “Noise-to-State Stability for a Class of Random Systems With State-Dependent Switching”]]>633910910156<![CDATA[Introducing IEEE Collabratec]]>6339119111858<![CDATA[Become a published author in 4 to 6 weeks]]>633912912914<![CDATA[IEEE Control Systems Society]]>633C3C3166