Naval Postgraduate School

About: Naval Postgraduate School is a education organization based out in Monterey, California, United States. It is known for research contribution in the topics: Tropical cyclone & Nonlinear system. The organization has 5246 authors who have published 11614 publications receiving 298300 citations. The organization is also known as: NPS & U.S. Naval Postgraduate School.

Transformation of a Large Monsoon Depression to a Tropical Storm during TCM-93

Abstract: Data obtained during two aircraft observing periods (AOP) from the TCM-93 mini field experiment are used to describe the transformation between 5° and 10°N of a large depression in the western North Pacific monsoon trough into a tropical cyclone over a 36-h period. The transformation is defined to occur in three stages. Although a large mesoscale convective system (MCS) was present along the eastern periphery of the monsoon depression during the preorganization stage characterized by observations from the first AOP, the overall convective organization of the broad circulation is weak. The structure of the MCS provided a midlevel subsynoptic contribution to the vorticity of the monsoon depression and contributed to a shift in the center of the monsoon depression circulation between 800 and 600 mb toward the MCS location. However, the presence of unsaturated downdrafts associated with the MCS perturbed the low-level thermodynamic conditions and contributed to the rapid decay of the MCS. Slow intens...

Optimal Synchronization of Heterogeneous Nonlinear Systems With Unknown Dynamics

Abstract: Optimal output synchronization of multi-agent leader–follower systems with unknown nonlinear dynamics is considered. The agents are assumed heterogeneous so that the dynamics may be nonidentical. A distributed observer is designed to estimate the leader state for each agent. A discounted performance function is defined for each agent, and an augmented Hamilton–Jacobi–Bellman (HJB) equation is derived to find its minimal value. The HJB solution depends on the trajectories of the local state and the distributed observer state. A control protocol based on the HJB solution assures that the synchronization error goes to zero locally asymptotically fast for all agents. The proposed approach has two main advantages compared to standard output synchronization methods. First, it is optimal in the sense that it not only makes the steady-state synchronization error zero, but also minimizes the transient error. Second, it does not require the explicit solution to the output regulator equations, though the HJB solutions implicitly provide optimal solutions to them. Finally, a reinforcement learning technique is used to learn the optimal control protocol for each agent without requiring any knowledge of the agents or the leader dynamics. Simulation studies on a notional multi-agent system validate the proposed approach.

Two-stage electoral competition in two-party contests: persistent divergence of party positions

Abstract: Models of party competition building on Downs (1957) have recognized that there are centrifugal and centripetal forces in party competition; but one such force, the existence of party primaries, has been remarkably neglected in recent literature. We consider party/candidate policy divergence in two-party competition in one dimension where there is a two-stage electoral process, e.g., a primary election (or caucus) among party supporters to select that party’s candidate followed by a general election. We develop a model in which (some or all) voters in the primary election are concerned with the likelihood that the primary victor will be able to win the general election and being concerned with that candidate’s policy position. This model is similar in all but technical details to that given in an almost totally neglected early paper in Public Choice Coleman (1971) 11:35–60, but we offer important new results on electoral dynamics for candidate locations. In addition to accounting for persistent party divergence by incorporating a more realistic model of the institutions that govern elections in the U.S., the model we offer gives rise to predictions that match a number of important aspects of empirical reality such as frequent victories for incumbents and greater than otherwise expected electoral success for the minority party in situations where that party has its supporters more closely clustered ideologically than the supporters of the larger party (in particular, with a concentration of voters between the party mean and the population mean).

The use of latent semantic analysis in operations management research

Abstract: In this article, we introduce the use of Latent Semantic Analysis (LSA) as a technique for uncovering the intellectual structure of a discipline. LSA is an emerging quantitative method for content analysis that combines rigorous statistical techniques and scholarly judgment as it proceeds to extract and decipher key latent factors. We provide a stepwise explanation and illustration for implementing LSA. To demonstrate LSA's ability to uncover the intellectual structure of a discipline, we present a study of the field of Operations Management. We also discuss a number of potential applications of LSA to show how it can be used in empirical Operations Management research, specifically in areas that can benefit from analyzing large volumes of unstructured textual data.

Low-Thrust, High-Accuracy Trajectory Optimization

Abstract: J OURNAL OF G UIDANCE , C ONTROL , AND D YNAMICS Vol. 30, No. 4, July–August 2007 Low-Thrust, High-Accuracy Trajectory Optimization I. Michael Ross, ∗ Qi Gong, † and Pooya Sekhavat ‡ Naval Postgraduate School, Monterey, California 93943 DOI: 10.2514/1.23181 Multirevolution, very low-thrust trajectory optimization problems have long been considered difficult problems due to their large time scales and high-frequency responses. By relating this difficulty to the well-known problem of aliasing in information theory, an antialiasing trajectory optimization method is developed. The method is based on Bellman’s principle of optimality and is extremely simple to implement. Appropriate technical conditions are derived for generating candidate optimal solutions to a high accuracy. The proposed method is capable of detecting suboptimality by way of three simple tests. These tests are used for verifying the optimality of a candidate solution without the need for computing costates or other covectors that are necessary in the Pontryagin framework. The tests are universal in the sense that they can be used in conjunction with any numerical method whether or not antialiasing is sought. Several low-thrust example problems are solved to illustrate the proposed ideas. It is shown that the antialiased solutions are, in fact, closed-loop solutions; hence, optimal feedback controls are obtained without recourse to the complexities of the Hamilton–Jacobi theory. Because the proposed method is easy to implement, it can be coded on an onboard computer for practical space guidance. the field to exchange ideas over several workshops. These workshops, held over 2003–2006, further clarified the scope of the problems, and ongoing efforts to address them are described in [12]. From a practical point of view, the goal is to quickly obtain verifiably optimal or near-optimal solutions to finite- and low-thrust problems so that alternative mission concepts can be analyzed I. Introduction C ONTINUOUS-THRUST trajectory optimization problems have served as one of the motivating problems for optimal control theory since its inception [1–4]. The classic problem posed by Moyer and Pinkham [2] is widely discussed in textbooks [1,3,4] and research articles [5–7]. When the continuity of thrust is removed from such problems, the results can be quite dramatic as illustrated in Fig. 1. This trajectory was obtained using recent advances in optimal control techniques and is extensively discussed in [8]. In canonical units, the problem illustrated in Fig. 1 corresponds to doubling the semimajor axis (a 0 1, a f 2), doubling the eccentricity (e 0 0:1, e f 0:2), and rotating the line of apsides by 1 rad. Note that the extremal thrust steering program for minimizing fuel is not tangential over a significant portion of the trajectory. Furthermore, the last burn is a singular control as demonstrated in Fig. 2 by the vanishing of the switching function. Although such finite-thrust problems can be solved quite readily nowadays, it has long been recognized [9–11] that as the thrust authority is reduced, new problems emerge. These well-known challenges chiefly arise as a result of a long flight time measured in terms of the number of orbital revolutions. Consequently, such problems are distinguished from finite-thrust problems as low-thrust problems although the boundary between finite thrust and low thrust is not altogether sharp. Although ad hoc techniques may circumvent some of the low- thrust challenges, it is not quite clear if the solutions generated from such methods are verifiably optimal. As detailed in [8], the engineering feasibility of a space mission is not dictated by trajectory generation, but by optimality. This is because fuel in space is extraordinarily expensive as the cost of a propellant is driven by the routine of space operations, or the lack of it, and not the chemical composition of the fuel. In an effort to circumvent ad hoc techniques to efficiently solve emerging problems in finite- and low-thrust trajectory optimization, NASA brought together leading experts in al Or iti bit In it Fin rb al O Transfer Trajectory Fig. 1 A benchmark minimum-fuel finite-thrust orbit transfer problem. Thrust Acceleration, u s = 0 Switching Function, s Received 13 February 2006; accepted for publication 21 August 2006. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. Copies of this paper may be made for personal or internal use, on condition that the copier pay the $10.00 per- copy fee to the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923; include the code 0731-5090/07 $10.00 in correspondence with the CCC. Professor, Department of Mechanical and Astronautical Engineering; imross@nps.edu. Associate Fellow AIAA. Research Associate, Department of Mechanical and Astronautical Engineering; qgong@nps.edu. Research Scientist, Department of Mechanical and Astronautical Engineering; psekhava@nps.edu. Singular Control s u time (canonical units) Fig. 2 Extremal thrust acceleration (control) program t7 !u and the corresponding switching function t7 !s for the trajectory shown in Fig. 1.