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The NDP measures contamination, plasma characteristics, electrical fields, and magnetic fields. This paper describes the NDP requirements, development process, and flight systems functionality.
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Zames (1981) has observed that there is, in general, no 'separation principle' to guarantee optimality of a division between control law design and filtering of plant uncertainty. Peczkowski and Sain (1978) have solved a model matching problem using transfer functions. Taking into consideration this investigation, Peczkowski et al. (1979) proposed the Total Synthesis Problem (TSP), wherein both the command/output-response and command/control-response are to be synthesized, subject to the plant constraint. The TSP concept can be subdivided into a Nominal Design Problem (NDP), which is not dependent upon specific controller structures, and a Feedback Synthesis Problem (FSP), which is. Gejji (1980) found that NDP was characterized in terms of the plant structural matrices and a single, 'good' transfer function matrix. Sain et al. (1981) have extended this NDP work. The present investigation is concerned with a study of FSP for the unity feedback case. NDP, together with feedback synthesis, is understood as a Total Synthesis Problem.
The Nominal Design Problem (NDP) is extended to nonlinear cases, and a new case study of robust feedback synthesis for gas turbine control design is presented. The discussion of NDP extends and builds on earlier Total Synthesis Problem theory and ideas. Some mathematical preliminaries are given in which a bijection from a set S onto a set T is considered, with T admitting the structure of an F-vector space. NDP is then discussed for a nonlinear plant, and nonlinear nominal design is defined and characterized. The design of local controllers for a turbojet and the scheduling of these controls into a global control are addressed.
The GRAVNET system is based on a medium frequency (MF) radar (2.22 MGz) with one site consisting of a transmitting and spaced receiving antenna; and two remote receiving sites (approximately 40 km distance, forming an approximately equalateral triangle), also spaced receiving antennas. The winds of the upper middle atmosphere (60 to 110 km) are measured at each of the three sites in real time, using the Spaced Antenna method. Up to 12 profiles per hour were obtained. Spectral analysis was performed separately on northward and eastward velocity components for each site at the same height. Cross spectra are then found between sites. Data selection criteria included the Normalized Phase Discrepancy (NDP).
The Deep Space 1 (DS1) mission has successfully validated the use of ion propulsion technology for interplanetary spacecraft. The NASA Solar Electric Propulsion (SEP) Technology Applications Readiness (NSTAR) Project developed the Ion Propulsion Subsystem (IPS) for DS1. As part of the NSTAR validation effort, the NSTAR Project included a diagnostics element to characterize the local environment produced during IPS operations and its effects on spacecraft subsystems and science instruments. An integrated, comprehensive set of diagnostics, the NSTAR Diagnostics Package (NPD) was developed and operated on DS1 to characterize the IPS environment. The DS1 Spacecraft Team officially assigned the name “IPS Diagnostics Subsystems (IDS)” to the NDP for the DS1 mission. During the technology validation phase of the DS1 mission, a large amount of data was collected from the IDS under a variety of IPS operating conditions. IDS was able to characterize the contamination environment, charge-exchange xenon ion and electron population and energies, plasma noise and electromagnetic noise, and magnetic fields associated with IPS. The results presented here describe the charge-exchange plasma, contamination, plasma wave/EMI, and DC magnetic environments critical to designers of future space missions using ion propulsion