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ANFIS and MPC controllers for a reconfigurable lower limb exoskeleton

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Abstract

The exoskeletons are robotic active orthoses intended to enhance power or in medical applications as rehabilitation and assistive walking. In the context of designing a controller for the reconfigurable exoskeleton for lower limb, it is critical to define the hardware as well as the control. The scope of this work was to define the controller for reconfigurable exoskeleton using three types of controllers: PD, ANFIS, and MPC. The PD controllers are the typical approach for torque/tracking control while artificial intelligence controller, as ANFIS, and optimal controller, as MPC, are recently entering to this field. The ANFIS and MPC controllers may bring more precision and capability to distribute the processing operations. Afterward, this work contrasts the performance evaluation using objective indices to evaluate the error, ISE, IAE, ITSE, ITAE, ISTSE, and ISTAE. The results suggest that ANFIS and MPC controllers have the potential to drive the torque/traction reducing the error while having the capability to learn from the disturbances from the surroundings.

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Acknowledgments

The authors want to acknowledge Tecnologico de Monterrey for all the support during this research.

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Authors and Affiliations

  1. Tecnologico de Monterrey, 14380, Mexico, DF, Mexico

    Carlos A. Rodriguez, Pedro Ponce & Arturo Molina

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  1. Carlos A. Rodriguez
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  2. Pedro Ponce
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  3. Arturo Molina
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Correspondence to Carlos A. Rodriguez.

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Carlos Alfonso Rodriguez Sierra, Pedro Ponce, and Arturo Molina declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by H. Ponce.

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Rodriguez, C.A., Ponce, P. & Molina, A. ANFIS and MPC controllers for a reconfigurable lower limb exoskeleton. Soft Comput 21, 571–584 (2017). https://doi.org/10.1007/s00500-016-2321-9

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