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Conference papers

Improving Operator Performance through the Use of a Multivariable Human-Machine Control Strategy

Abstract : Most of the mechatronics equipments and gadgets that we all nowadays rely on incorporate some kind of multidimensional human-machine systems. There is an increasing concern for improving the usability, performance, ergonomics and safety of such devices, and ultimately this will lead to the mass-production of next-generation intelligent machines, which will be capable to assist the human operator and to reduce the global effort by estimating and measuring its skills. This ongoing work introduces a novel human-machine multi-dynamic modeling methodology which can be applied on the development of these Human Adaptive Mechatronic (HAM) machines, able to adapt to the skill/dexterity levels of its users, and to enhance Human’s proficiency. As a new strategy for model development, a number of two-dimensional independent pursuit manual tracking experiments are evaluated. A human-machine state-space linear model is obtained and successfully applied to design an improved closed-loop multivariable control structure.
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Rui Antunes, Fernando V. Coito, Hermínio Duarte-Ramos. Improving Operator Performance through the Use of a Multivariable Human-Machine Control Strategy. 3rd Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Feb 2012, Costa de Caparica, Portugal. pp.95-104, ⟨10.1007/978-3-642-28255-3_11⟩. ⟨hal-01365574⟩

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