2,105 research outputs found
Parameterised function ILC with application to stroke rehabilitation
No full textFunctional electrical stimulation (FES) is a popular assistive technology that uses electrical impulses to artificially stimulate muscles to help paralysed or impaired subjects regain their lost movement after stroke. A large number of FES elements can be combined to form FES arrays which are capable of activating the multiple muscles needed to perform functional arm movements. However, the control of FES arrays is challenging since high precision is required but there is little time available in a clinical or home setting to identify a model. To date, by far the highest accuracy has been achieved using iterative learning control (ILC), a technique that mirrors the repeated nature of rehabilitation task practice. In particular, high accuracy has been achieved using a well-known ILC law for a general class of nonlinear systems which computes the updated control input using a linearised plant model. Since a global system model is unavailable, this is identified on every ILC trial by running an identification test. This adds many time-consuming identification tests, making it infeasible for clinical deployment. To solve this problem, an approach is developed that can deliver high accuracy with minimal identification overhead. It introduces a parameterised plant model that is updated in parallel with the ILC using all available data, and then applied to replace identification tests. Rigorous conditions are derived to ensure convergence is preserved while minimising identification time. Numerical results show that four references can be tracked using only 10.8% of the experimental tests required by standard ILC algorithms. The approach is then applied experimentally to six unimpaired subjects using a realistic rehabilitation scenario. In particular, a novel stereo camera system is used to measure hand joint angles in a manner that can transfer to home use. Results show mean joint angle tracking accuracy within 5°, while requiring only between 25% and 64.9% of the experimental tests of standard ILC.</p
Robust iterative learning control for unstable MIMO systems
No full textIterative learning control (ILC) is a well-established technique to successively improve tracking accuracy for systems that repeatedly perform the same task. Most current literature imposes constraints on the nature of the system, such as requiring it to be full-rank, or inherently stable. This paper presents a generalised ILC framework that can handle non-linear, unstable, MIMO systems with rank deficiency. This involves the minimisation of a cost function that balances tracking performance and input effort, extending previous approaches to include a 'robustness filter' within the optimisation. Gap metric analysis is then applied to examine the robustness of the resulting system, with performance bounds derived for both serial and parallel ILC architectures. A design procedure is presented that allows the designer to transparently trade-off robustness and convergence properties. The design framework is illustrated via application to the inverted pendulum problem, a classic example of a highly nonlinear, unstable, and under-actuated system
Experimentally validated continuous-time repetitive control of non-minimum phase plants with a prescribed degree of stability
Get PDFThis paper considers the application of continuous-time repetitive control to non-minimum phase plants in a continuous-time model predictive control setting. In particular, it is shown how some critical performance problems associated with repetitive control of such plants can be avoided by use of predictive control with a prescribed degree of stability. The results developed are first illustrated by simulation studies and then through experimental tests on a non-minimum phase electro-mechanical system
Multiple model iterative learning control of FES electrode arrays
No full textStroke is a common cause of hand and upper limb disability, but current rehabilitation approaches do not adequately support successful recovery. Functional electrical stimulation (FES) is the most widely used assistive technology, and is able to support accurate hand and wrist motion when applied using multi-element electrode arrays. However, accurate movements have only been possible using an iterative learning control (ILC) approach involving many repeated model identification tests. This lengthy process limits wide-spread use. This paper presents a solution for FES electrode array control using estimation-based multiple-model ILC (EM-MILC), in which a set of parameterised models is used to automatically update the stimulation applied to each array element every time a task is carried out. This removes the need for model identification, significantly improving system usability whilst maintaining high performance. Experimental results demonstrate that EM-MILC reduces the average number of tests from 16 to 3, compared to the most accurate existing approach
Iterative learning control of functional electrical stimulation electrode arrays
No full textStroke often causes weakness, paralysis, or loss of coordination in the hand and wrist, making it difficult to perform everyday tasks. Current rehabilitation approaches do not adequately assist patients in regaining their lost function, however it is possible to produce accurate hand and wrist gestures by artificially stimulating muscles using functional electrical stimulation (FES) applied to multi-element electrode arrays. This has been possible using iterative learning control (ILC), however it required lengthy model identification tests, and accuracy degraded due to fatigue, spasticity and changes in array position. This paper develops a new FES electrode array control framework which maintains high accuracy despite uncertain and potentially time-varying dynamics. First a model of stimulated hand and wrist dynamics embedding FES array misalignment is developed, and robust stability properties are derived using the gap metric. A compensating controller is then proposed to ameliorate array misalignment, and this is integrated within a powerful framework termed estimation-based multiple-model ILC (EMMILC), which automatically updates the underlying model to maintain performance in the presence of uncertain and changing dynamics. It is shown that EMMILC can remove the need for model identification, whilst maintaining high performance. This significantly improves the usability of FES arrays and opens up the possibility of bringing effective therapy to millions of patients in their own homes. Experimental results reveal that the proposed controller reduces the average converged error norm to 31.3\% of that obtained using existing model-based ILC
Manzanar camp map, "Manzanar, a photograph essay"
No full textA map of "Manzanar Relocation Center" reproduced from "Manzanar pilgrimage program" by hand by Chris S. Uyemura. The caption reads, "General plan of the W.R.A. Camp at Manzanar, California. Chris Uyemura Collection." A page from: Manzanar, a photograph essay (csudh_uye_0001).The Chris S. Uyemura Manzanar Photograph Collection consists of a pictorial essay, “Manzanar, a photographic essay,” and additional loose photos, which were compiled and collected by Chris S. Uyemura. The essay contains photographs, texts, and newspaper clippings, and was submitted to Professor Donald T. Hata of the Department of History at CSU Dominguez Hills. The collection depicts the incarceration of people of Japanese ancestry in the Manzanar camp during World War II as well as reflects the events, contrasting with photographs of the Manznar National Historic Site, which illustrates what is left of the camp today. The collection was originally named as “Asian Pacific Studies Collection Box 14.
Writers Talk featuring Chris Sunami
No full textChris Sunami describes writers and performers who will be at the Columbus Invitational Artists Competition. OSU student TJ Armstrong reviews two new Batman books: Batmobile: The Complete History and The Dark Knight Manual. And Ohio paranormal author John B. Kachuba describes what's scary about the Buckeye State.The media can be accessed here: http://streaming.osu.edu/knowledgebank/WritersTalk-Audio/WT_2012-8-6_sunami-kuchaba-batman.mp3Ohio State University. Center for the Study and Teaching of Writin
Introduction, "Manzanar, a photograph essay"
No full textIntroduction of his photographic essay, "Manzanar, a photographic essay" (csudh_uye_0001). "... to convey to the observer, the conditions in which the evacuees lived, the sights which they way, everyday, for those emotion filled years, and the memories of those years, carved in Limestone ..... to last forever."The Chris S. Uyemura Manzanar Photograph Collection consists of a pictorial essay, “Manzanar, a photographic essay,” and additional loose photos, which were compiled and collected by Chris S. Uyemura. The essay contains photographs, texts, and newspaper clippings, and was submitted to Professor Donald T. Hata of the Department of History at CSU Dominguez Hills. The collection depicts the incarceration of people of Japanese ancestry in the Manzanar camp during World War II as well as reflects the events, contrasting with photographs of the Manznar National Historic Site, which illustrates what is left of the camp today. The collection was originally named as “Asian Pacific Studies Collection Box 14.
Issei, "Manzanar, a photograph essay"
No full textA photograph of an Issei man, a Japanese immigrant, with chrysanthemums. Also includes an essay about the Issei. A page from: Manzanar, a photograph essay (csudh_uye_0001).The Chris S. Uyemura Manzanar Photograph Collection consists of a pictorial essay, “Manzanar, a photographic essay,” and additional loose photos, which were compiled and collected by Chris S. Uyemura. The essay contains photographs, texts, and newspaper clippings, and was submitted to Professor Donald T. Hata of the Department of History at CSU Dominguez Hills. The collection depicts the incarceration of people of Japanese ancestry in the Manzanar camp during World War II as well as reflects the events, contrasting with photographs of the Manznar National Historic Site, which illustrates what is left of the camp today. The collection was originally named as “Asian Pacific Studies Collection Box 14.
Gravestone in cemetery, "Manzanar, a photograph essay: Manzanar today"
No full textA photograph of gravestone in cemetery. Engraved name reads: Ogata Toshiro, Baby Jerry Ogata. A page from: Manzanar, a photograph essay (csudh_uye_0001).The Chris S. Uyemura Manzanar Photograph Collection consists of a pictorial essay, “Manzanar, a photographic essay,” and additional loose photos, which were compiled and collected by Chris S. Uyemura. The essay contains photographs, texts, and newspaper clippings, and was submitted to Professor Donald T. Hata of the Department of History at CSU Dominguez Hills. The collection depicts the incarceration of people of Japanese ancestry in the Manzanar camp during World War II as well as reflects the events, contrasting with photographs of the Manznar National Historic Site, which illustrates what is left of the camp today. The collection was originally named as “Asian Pacific Studies Collection Box 14.
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