Decentralized Formation Control with A Quadratic Lyapunov Function

In this paper, we investigate a decentralized formation control algorithm for an undirected formation control model. Unlike other formation control problems where only the shape of a configuration counts, we emphasize here also its Euclidean embedding. By following this decentralized formation control law, the agents will converge to certain equilibrium of the control system. In particular, we show that there is a quadratic Lyapunov function associated with the formation control system whose unique local (global) minimum point is the target configuration. In view of the fact that there exist multiple equilibria (in fact, a continuum of equilibria) of the formation control system, and hence there are solutions of the system which converge to some equilibria other than the target configuration, we apply simulated annealing, as a heuristic method, to the formation control law to fix this problem. Simulation results show that sample paths of the modified stochastic system approach the target configuration

On the Coordinate System of Space-Weather HMI Active Region Patches (SHARPs): A Technical Note

We describe the coordinate systems of two streams of HMI active region vector data. A distinction is made between (a) the 2D grid on which the field vector is measured (or sampled), and (b) the 3D coordinate established at each grid point, in which the field vector is presented. The HMI data reduction can involve coordinate changes on both, with those performed on the former termed "remapping", the latter "vector transformation". Relevant pipeline procedures are described. Useful examples are given for data analysis.Comment: Technical note for the HMI vector data pipeline. Containing data analysis example. Corrected typo in Eq(6

On Coding Efficiency for Flash Memories

Recently, flash memories have become a competitive solution for mass storage. The flash memories have rather different properties compared with the rotary hard drives. That is, the writing of flash memories is constrained, and flash memories can endure only limited numbers of erases. Therefore, the design goals for the flash memory systems are quite different from these for other memory systems. In this paper, we consider the problem of coding efficiency. We define the "coding-efficiency" as the amount of information that one flash memory cell can be used to record per cost. Because each flash memory cell can endure a roughly fixed number of erases, the cost of data recording can be well-defined. We define "payload" as the amount of information that one flash memory cell can represent at a particular moment. By using information-theoretic arguments, we prove a coding theorem for achievable coding rates. We prove an upper and lower bound for coding efficiency. We show in this paper that there exists a fundamental trade-off between "payload" and "coding efficiency". The results in this paper may provide useful insights on the design of future flash memory systems.Comment: accepted for publication in the Proceeding of the 35th IEEE Sarnoff Symposium, Newark, New Jersey, May 21-22, 201