Three degree-of-freedom force feedback control for robotic mating of umbilical lines

The use of robotic manipulators for the mating and demating of umbilical fuel lines to the Space Shuttle Vehicle prior to launch is investigated. Force feedback control is necessary to minimize the contact forces which develop during mating. The objective is to develop and demonstrate a working robotic force control system. Initial experimental force control tests with an ASEA IRB-90 industrial robot using the system's Adaptive Control capabilities indicated that control stability would by a primary problem. An investigation of the ASEA system showed a 0.280 second software delay between force input commands and the output of command voltages to the servo system. This computational delay was identified as the primary cause of the instability. Tests on a second path into the ASEA's control computer using the MicroVax II supervisory computer show that time delay would be comparable, offering no stability improvement. An alternative approach was developed where the digital control system of the robot was disconnected and an analog electronic force controller was used to control the robot's servosystem directly, allowing the robot to use force feedback control while in rigid contact with a moving three-degree-of-freedom target. An alternative approach was developed where the digital control system of the robot was disconnected and an analog electronic force controller was used to control the robot's servo system directly. This method allowed the robot to use force feedback control while in rigid contact with moving three degree-of-freedom target. Tests on this approach indicated adequate force feedback control even under worst case conditions. A strategy to digitally-controlled vision system was developed. This requires switching between the digital controller when using vision control and the analog controller when using force control, depending on whether or not the mating plates are in contact

Plagiarism and Citing Sources - AMA

This module will provide rules and examples for citing sources in AMA citation style.https://digitalcommons.usu.edu/elearning_all/1053/thumbnail.jp

Online Learning Platforms - When to Use

This handout provides an overview of online learning platforms adopted by the USU Libraries to support university instruction.https://digitalcommons.usu.edu/elearning_all/1001/thumbnail.jp

Avoiding Plagiarism in APA

Tutorial for avoiding plagiarism in APA 7th Edition citation style. This provides examples, resources, and tips.https://digitalcommons.usu.edu/elearning_all/1044/thumbnail.jp

A Hybrid Observer for a Distributed Linear System with a Changing Neighbor Graph

A hybrid observer is described for estimating the state of an $m>0$ channel, $n$-dimensional, continuous-time, distributed linear system of the form $\dot{x} = Ax,\;y_i = C_ix,\;i\in\{1,2,\ldots, m\}$. The system's state $x$ is simultaneously estimated by $m$ agents assuming each agent $i$ senses $y_i$ and receives appropriately defined data from each of its current neighbors. Neighbor relations are characterized by a time-varying directed graph $\mathbb{N}(t)$ whose vertices correspond to agents and whose arcs depict neighbor relations. Agent $i$ updates its estimate $x_i$ of $x$ at "event times" $t_1,t_2,\ldots$ using a local observer and a local parameter estimator. The local observer is a continuous time linear system whose input is $y_i$ and whose output $w_i$ is an asymptotically correct estimate of $L_ix$ where $L_i$ a matrix with kernel equaling the unobservable space of $(C_i,A)$. The local parameter estimator is a recursive algorithm designed to estimate, prior to each event time $t_j$, a constant parameter $p_j$ which satisfies the linear equations $w_k(t_j-\tau) = L_kp_j+\mu_k(t_j-\tau),\;k\in\{1,2,\ldots,m\}$, where $\tau$ is a small positive constant and $\mu_k$ is the state estimation error of local observer $k$. Agent $i$ accomplishes this by iterating its parameter estimator state $z_i$, $q$ times within the interval $[t_j-\tau, t_j)$, and by making use of the state of each of its neighbors' parameter estimators at each iteration. The updated value of $x_i$ at event time $t_j$ is then $x_i(t_j) = e^{A\tau}z_i(q)$. Subject to the assumptions that (i) the neighbor graph $\mathbb{N}(t)$ is strongly connected for all time, (ii) the system whose state is to be estimated is jointly observable, (iii) $q$ is sufficiently large, it is shown that each estimate $x_i$ converges to $x$ exponentially fast as $t\rightarrow \infty$ at a rate which can be controlled.Comment: 7 pages, the 56th IEEE Conference on Decision and Contro

Could the p75 Neurotrophin Receptor p75NTR Help Unlock the Mysteries of Infertility?

Histology is the study of microscopic tissue structures that examines the correlation between structure and function. This technique was utilized when analyzing the biological processes of folliculogenesis and oogenesis. These processes study the maturation of the ovarian follicle and production of an ovum, respectively. The p75 neurotrophin receptor (p75NTR)has been identified to contribute to the maturation of ovarian follicles, but the role of p75NTR in ovulation remains unknown. To investigate the role of p75NTR in ovulation, an animal study analyzing the histology of the mouse ovary was conducted. In this study, the number of primary follicles, secondary follicles, antral follicles, and corpus luteum were analyzed in wild type mice and then compared to the follicles present in genetically modified mice that lacked the p75NTRgene (p75 knock out (p75KO) mice). When the mice in this study reached eight weeks of age, the mice were killed, and their reproductive tissues were collected. Upon harvest, the tissues were processed for sectioning and then stained for analysis. Microscopic analysis revealed that there was a significant relationship between the number of corpus luteum present in the wild type mice compared to the knockout mice (p=0.006). Indicating that wildtype mice are ovulating at higher rates than p75KO mice. This data supports that p75NTR is playing an active role in the ovulatory process