Abstract
This paper presents a control scheme for the humanoid robot TEO’s elbow joint based on a novel tuning method for fractional-order PD and PI controllers. Due to the graphical nature of the proposed method, a few basic operations are enough to tune the controllers, offering very competitive results compared to classic methods. The experiments show a robust performance of the system to mass changes at the tip of the humanoid arm.
Highlights
Fractional Calculus (FC) has been used with success in quite di®erentelds, from economics[1] to physics,[2] and engineering, with applications in modeling and system control.[3,4]The fractional-order controllers receiving the most attention in the last decades are the Fractional Proportional Integral Derivative (PID) controllers, formulated for therst time by Podlubny et al.[5] and later studied in di®erent works.[6,7,8]A remarkable number of articles, specially when the subject involves motion control, focus on the derivative control, leaving the integrator out
The purpose of this work is to propose a strategy for the control of the elbow joint of the humanoid robot TEO (Fig. 1), a robot built by the Robotics Lab team of Carlos III University of Madrid
The arm will move through a descending trajectory, starting at 60 [deg], that will be the worst case of uncertainty, as the gravity will act in opposition to the control e®ort
Summary
A remarkable number of articles, specially when the subject involves motion control, focus on the derivative control, leaving the integrator out This control scheme has the advantage of using the position sensor as an integrator, which simplies the controller, while the steady state error is still canceled, making the integral part unnecessary, even undesired. Therst to use this kind of fractional controller was Dorcak et al.,[9] and others,[10,11] with application to the control of the joints. 12–14 the last approach is applied to a legged robot Similar approaches have been proposed in Refs. 12–14 the last approach is applied to a legged robot
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