Lev V. Utkin, Sergey V. Gurov and Igor B. Shubinsky
Analyses computer integrated manufacturing systems with the real‐time constraints under the condition that time to repair depends on human experience and can be fuzzy. Proposes an…
Abstract
Analyses computer integrated manufacturing systems with the real‐time constraints under the condition that time to repair depends on human experience and can be fuzzy. Proposes an approach which combines probability and possibility measures. Illustrates the impact of the growth of human experience on the reliability characteristics with an application example.
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Most methods of reliability analysis of cold standby systems assume that the precise probability distributions of the component times to failure are available. However, this…
Abstract
Most methods of reliability analysis of cold standby systems assume that the precise probability distributions of the component times to failure are available. However, this assumption may be unreasonable in a wide scope of cases (software, human‐machine systems). Therefore, the imprecise reliability models of cold standby systems are proposed in the paper. These models suppose that arbitrary probability distributions of the component time to failure are possible and they are restricted only by available information in the form of lower and upper probabilities of some events. It is shown how the reliability assessments may vary with a type of available information. The impact of the independence condition on reliability of systems is studied. Numerical examples illustrate the proposed models.
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Rihab Bkekri, Anouar Benamor, Mohamed Amine Alouane, Georges Fried and Hassani Messaoud
Assistive technology products are designed to provide additional accessibility to individuals who have physical or cognitive difficulties, impairments and disabilities. The…
Abstract
Purpose
Assistive technology products are designed to provide additional accessibility to individuals who have physical or cognitive difficulties, impairments and disabilities. The purpose of this paper is to deal with the control of a knee joint orthosis intended to be used for rehabilitation and assistive purpose; this control aims to reduce the influence of the uncertainties and eliminating the external disturbances in the system.
Design/methodology/approach
This paper deals with the robust adaptive sliding mode controller (ASMC) of human-driven knee joint orthosis system with mismatched uncertainties and external disturbances. The shank-orthosis system has been modeled and its parameters have been identified. This control reduces the effect of parameter uncertainties and external disturbances on the system performance and improves the system robustness as results. The ASMC was designed to offer the possibility to track the state of the reference model. Moreover, the Lyapunov stability theory was used to study the asymptotical stability of the ASMC.
Findings
The advantage of the robust ASMC method is the tracking precision and reducing the required time for eliminating external disturbances and uncertainties. The experimental results show in real-time in terms of stability and present that the advantages of this control approach are the position tracking and robustness.
Originality/value
In this paper, to deal with the parameter uncertainties of the human-driven knee joint orthosis, an ASMC was successfully applied based on sliding mode and Lyapunov stability theory. It has good dynamic response and tracking performance. Besides, the adaptive algorithm is simple, easy to achieve and has good adaptability and robustness against the parameter variations and external disturbances. The design technique is simple and efficient. The development of this control takes into consideration the perturbation, allowing to track a desired trajectory.