Shil'nikov Chaos control using Homoclinic orbits and the Newhouse region

A method of controlling Shil'nikov's type chaos using windows that appear in the 1 dimensional bifurcation diagram when perturbations are applied, and using existence of stable homoclinic orbits near the unstable one is presented and applied to the electronic Chua's circuit. A demonstration of the chaos control in the electronic circuit experiments and their simulations and bifurcation analyses are given.Comment: 23 pages, 48 figure

Achievable and Crystallized Rate Regions of the Interference Channel with Interference as Noise

The interference channel achievable rate region is presented when the interference is treated as noise. The formulation starts with the 2-user channel, and then extends the results to the n-user case. The rate region is found to be the convex hull of the union of n power control rate regions, where each power control rate region is upperbounded by a (n-1)-dimensional hyper-surface characterized by having one of the transmitters transmitting at full power. The convex hull operation lends itself to a time-sharing operation depending on the convexity behavior of those hyper-surfaces. In order to know when to use time-sharing rather than power control, the paper studies the hyper-surfaces convexity behavior in details for the 2-user channel with specific results pertaining to the symmetric channel. It is observed that most of the achievable rate region can be covered by using simple On/Off binary power control in conjunction with time-sharing. The binary power control creates several corner points in the n-dimensional space. The crystallized rate region, named after its resulting crystal shape, is hence presented as the time-sharing convex hull imposed onto those corner points; thereby offering a viable new perspective of looking at the achievable rate region of the interference channel.Comment: 28 pages, 12 figures, to appear in IEEE Transactions of Wireless Communicatio

Convex computation of the region of attraction of polynomial control systems

We address the long-standing problem of computing the region of attraction (ROA) of a target set (e.g., a neighborhood of an equilibrium point) of a controlled nonlinear system with polynomial dynamics and semialgebraic state and input constraints. We show that the ROA can be computed by solving an infinite-dimensional convex linear programming (LP) problem over the space of measures. In turn, this problem can be solved approximately via a classical converging hierarchy of convex finite-dimensional linear matrix inequalities (LMIs). Our approach is genuinely primal in the sense that convexity of the problem of computing the ROA is an outcome of optimizing directly over system trajectories. The dual infinite-dimensional LP on nonnegative continuous functions (approximated by polynomial sum-of-squares) allows us to generate a hierarchy of semialgebraic outer approximations of the ROA at the price of solving a sequence of LMI problems with asymptotically vanishing conservatism. This sharply contrasts with the existing literature which follows an exclusively dual Lyapunov approach yielding either nonconvex bilinear matrix inequalities or conservative LMI conditions. The approach is simple and readily applicable as the outer approximations are the outcome of a single semidefinite program with no additional data required besides the problem description

Sharing of heteroplasmies between human liver lobes varies across the mtDNA genome

Mitochondrial DNA (mtDNA) heteroplasmy (intra-individual variation) varies among different human tissues and increases with age, suggesting that the majority of mtDNA heteroplasmies are acquired, rather than inherited. However, the extent to which heteroplasmic sites are shared across a tissue remains an open question. We therefore investigated heteroplasmy in two liver samples (one from each primary lobe) from 83 Europeans, sampled at autopsy. Minor allele frequencies (MAF) at heteroplasmic sites were significantly correlated between the two liver samples from an individual, with significantly more sharing of heteroplasmic sites in the control region than in the non-control region. We show that this increased sharing for the control region cannot be explained by recent mutations at just a few specific heteroplasmic sites or by the possible presence of 7S DNA. Moreover, we carried out simulations to show that there is significantly more sharing than would be predicted from random genetic drift from a common progenitor cell. We also observe a significant excess of non-synonymous vs. synonymous heteroplasmies in the protein-coding region, but significantly more sharing of synonymous heteroplasmies. These contrasting patterns for the control vs. the non-control region, and for non-synonymous vs. synonymous heteroplasmies, suggest that selection plays a role in heteroplasmy sharing

Entanglement in the anisotropic Heisenberg XYZ model with different Dzyaloshinskii-Moriya interaction and inhomogeneous magnetic field

We investigate the entanglement in a two-qubit Heisenberg XYZ system with different Dzyaloshinskii-Moriya(DM) interaction and inhomogeneous magnetic field. It is found that the control parameters ($D_{x}$, $B_{x}$ and $b_{x}$) are remarkably different with the common control parameters ($D_{z}$,$B_{z}$ and $b_{z}$) in the entanglement and the critical temperature, and these x-component parameters can increase the entanglement and the critical temperature more efficiently. Furthermore, we show the properties of these x-component parameters for the control of entanglement. In the ground state, increasing $D_{x}$ (spin-orbit coupling parameter) can decrease the critical value $b_{xc}$ and increase the entanglement in the revival region, and adjusting some parameters (increasing $b_{x}$ and $J$, decreasing $B_{x}$ and $\Delta$) can decrease the critical value $D_{xc}$ to enlarge the revival region. In the thermal state, increasing $D_{x}$ can increase the revival region and the entanglement in the revival region (for $T$ or $b_{x}$), and enhance the critical value $B_{xc}$ to make the region of high entanglement larger. Also, the entanglement and the revival region will increase with the decrease of $B_{x}$ (uniform magnetic field). In addition, small $b_{x}$ (nonuniform magnetic field) has some similar properties to $D_{x}$, and with the increase of $b_{x}$ the entanglement also has a revival phenomenon, so that the entanglement can exist at higher temperature for larger $b_{x}$.Comment: 8 pages, 8 figure

A model predictive controller for robots to follow a virtual leader

SUMMARYIn this paper, we develop a model predictive control (MPC) scheme for robots to follow a virtual leader. The stability of this control scheme is guaranteed by adding a terminal state penalty to the cost function and a terminal state region to the optimization constraints. The terminal state region is found by analyzing the stability. Also a terminal state controller is defined for this control scheme. The terminal state controller is a virtual controller and is never used in the control process. Two virtual leader-following formation models are studied. Simulations on different formation patterns are provided to verify the proposed control strategy.</jats:p

Macroscopic modelling and robust control of bi-modal multi-region urban road networks

The paper concerns the integration of a bi-modal Macroscopic Fundamental Diagram (MFD) modelling for mixed traffic in a robust control framework for congested single- and multi-region urban networks. The bi-modal MFD relates the accumulation of cars and buses and the outflow (or circulating flow) in homogeneous (both in the spatial distribution of congestion and the spatial mode mixture) bi-modal traffic networks. We introduce the composition of traffic in the network as a parameter that affects the shape of the bi-modal MFD. A linear parameter varying model with uncertain parameter the vehicle composition approximates the original nonlinear system of aggregated dynamics when it is near the equilibrium point for single- and multi-region cities governed by bi-modal MFDs. This model aims at designing a robust perimeter and boundary flow controller for single- and multi-region networks that guarantees robust regulation and stability, and thus smooth and efficient operations, given that vehicle composition is a slow time-varying parameter. The control gain of the robust controller is calculated off-line using convex optimisation. To evaluate the proposed scheme, an extensive simulation-based study for single- and multi-region networks is carried out. To this end, the heterogeneous network of San Francisco where buses and cars share the same infrastructure is partitioned into two homogeneous regions with different modes of composition. The proposed robust control is compared with an optimised pre-timed signal plan and a single-region perimeter control strategy. Results show that the proposed robust control can significantly: (i) reduce the overall congestion in the network; (ii) improve the traffic performance of buses in terms of travel delays and schedule reliability, and; (iii) avoid queues and gridlocks on critical paths of the network