Title: Modelling and robust control of a soft robot based on conjugated polymer actuators

Authors: Amir Ali Amiri Moghadam; Majid Moavenian; Hamid Ekhteraee Toussi

Addresses: Faculty of Eng., Department of Mechanical Eng., Ferdowsi University of Mashhad, P.O. Box: 9177948944-11, Mashhad, Iran. ' Faculty of Eng., Department of Mechanical Eng., Ferdowsi University of Mashhad, P.O. Box: 9177948944-11, Mashhad, Iran. ' Faculty of Eng., Department of Mechanical Eng., Ferdowsi University of Mashhad, P.O. Box: 9177948944-11, Mashhad, Iran

Abstract: In this paper, modelling and robust control of a two segment robot arm made from polypyrrole is proposed. Conjugated polymer actuators can be employed to achieve micro and nano scale precision, having a wide range of application including biomimetic robots, and biomedical devices. They can operate with low voltage while producing large displacement, in comparison to robotic joints, they do not have friction or backlash, but on the other hand, they have highly uncertain and time-varying electro-chemo-mechanical dynamics, which makes accurate and robust control of the actuator difficult. This paper consists of two major parts. In the modelling part, first, a suitable dynamic model is developed using Golubev technique, then kinematic modelling of robot is presented. Adaptive neuro-fuzzy inference system (ANFIS) is employed successfully to solve the inverse kinematics problem for different trajectories; this is examined for horizontal line and elliptical trajectories. In the controlling part, the robust control QFT is applied to control the conjugated polymer actuator. Analysis of the design shows that QFT controller has consistent and robust tracking performance.

Keywords: conjugated polymer actuators; polypyrrole; PPy; soft robots; adaptive neuro-fuzzy inference system; ANFIS; uncertainty; quantitative feedback theory; QFT; robot arms; robot modelling; robot control; dynamic modelling; kinematic modelling; robust control; neural networks; fuzzy logic; inverse kinematics; tracking performance.

DOI: 10.1504/IJMIC.2011.042657

International Journal of Modelling, Identification and Control, 2011 Vol.14 No.3, pp.216 - 226

Available online: 23 Sep 2011 *

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