Search NASA⌕ Search
Home/Archive/NASA NTRS

NASA NTRS · 20210001571

Stable Direct Adaptive Periodic Control Using Only Plant Order Knowledge

Bayard, D.
View original source ↗Export metadata ↓

Abstract

The main contribution of this paper is to put stability requirements for convergence of direct adaptive periodic controllers on equal footing with requirements for indirect adaptive periodic control, as set forth by Lozano. The resulting stability condition is simply that the plant order is known a priori. No other prior plant knowledge is used (e.g., relative degree, high-frequency gain, etc.), and persistent excitation is not required. More importantly, no assumption or knowledge is required as to whether the plant is minimum or nonminimum phase. A numerical example is given to demonstrate the method, and some guidelines are given for improving the adaptive transient response.

Explore related subjects

sampling

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Bayard, D.. 1994-01-01. Stable Direct Adaptive Periodic Control Using Only Plant Order Knowledge. https://ntrs.nasa.gov/citations/20210001571

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

NASA NTRS2013

Wireline Deep Drill for the Exploration of Icy Bodies

One of the most pressing current questions in space science is whether life has ever arisen anywhere else in the universe. Water is a critical prerequisite for all life-as-we-know-it, thus the possible exploration targets for extraterrestrial life are bodies that have or had copious liquid: Mars, Europa, and Enceladus. Due to the oxidizing nature of Mars' surface, as well as subsurface liquid water reservoirs present on Europa and Enceladus, the search for evidence of existing life must likely focus on subsurface locations, at depths sufficient to support liquid water or retain biologic signatures. To address these questions, an Auto-Gopher sampler has been developed that is a wireline type drill. This drill is suspended on a tether and its motors and mechanisms are built into a tube that ends with a coring bit. The tether provides the mechanical connection to a rover/lander on a surface as well as power and data communication. Upon penetrating to a target depth, the drill is retracted from the borehole, the core is deposited into a sample transfer system, and the drill is lowered back into the hole. Wireline operation sidesteps one of the major drawbacks of traditional continuous drill string systems by obviating the need for multiple drill sections, which add significantly to the mass and the complexity of the system (i.e. penetration rate was 40 cm per hour). Drilling to 2 meter depth and recovering of cores every 10 cm took a total time of 15 hours (a single step of drilling 10 cm and retrieving the core was 45 minutes). Total energy to reach the 2 m depth was 500 Whr. The Weight on Bit was limited to less than 70 Newton. The core recovery was 100%.

sampling↗
NASA NTRS2011

Runtime Verification with State Estimation

We introduce the concept of Runtime Verification with State Estimation and show how this concept can be applied to estimate theprobability that a temporal property is satisfied by a run of a program when monitoring overhead is reduced by sampling. In such situations, there may be gaps in the observed program executions, thus making accurate estimation challenging. To deal with the effects of sampling on runtime verification, we view event sequences as observation sequences of a Hidden Markov Model (HMM), use an HMM model of the monitored program to "fill in" sampling-induced gaps in observation sequences, and extend the classic forward algorithm for HMM state estimation (which determines the probability of a state sequence, given an observation sequence) to compute the probability that the property is satisfied by an execution of the program. To validate our approach, we present a case study based on the mission software for a Mars rover. The results of our case study demonstrate high prediction accuracy for the probabilities computed by our algorithm. They also show that our technique is much more accurate than simply evaluating the temporal property on the given observation sequences, ignoring the gaps.

sampling↗