Modeling and Robust Iterative Learning Control of a Quadruped Robot

In this paper, adaptive fuzzy back-stepping controller for the tracking control of a nine-degree of freedom quadruped robot has been investigated. First, the backstepping controller has been designed and its inherent stability has been studied using the Lyapunov theory. Due to the unknown control coefficient in the back-stepping method, a fuzzy system has been employed to change these coefficients adaptively. The proposed method has been applied to the quadruped robot and path-tracking problem has been studied. The simulation results show good performance of the proposed controller as compared to the recently proposed methods in literature.

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“…The details of M(θ) , C(θ, θ) and G(θ) for a ninedegree of freedom quadruped robot moving in a sagittal plane, are given in [10]. B.…”

Section: A Swing Phasementioning

confidence: 99%

Stable walking of quadruped robots using fuzzy back-stepping approach

Shakourzadeh

Farrokhi

2014

2014 Second RSI/ISM International Conference on Robotics and Mechatronics (ICRoM)

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“…Since it only incorporates joints in sagittal planar motion then it is clear that the gait tracking performance is important. Some planar motion studies in sagittal plane to control quadruped robot have been conducted also in [12,13], but no real hardware implementation has been reported.…”

Section: Introductionmentioning

confidence: 99%

Gait Tracking Control of Quadruped Robot Using Differential Evolution Based Structure Specified Mixed SensitivityH∞Robust Control

Sutyasadi

Parnichkun

2016

Journal of Control Science and Engineering

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This paper proposed a control algorithm that guarantees gait tracking performance for quadruped robots. During dynamic gait motion, such as trotting, the quadruped robot is unstable. In addition to uncertainties of parameters and unmodeled dynamics, the quadruped robot always faces some disturbances. The uncertainties and disturbances contribute significant perturbation to the dynamic gait motion control of the quadruped robot. Failing to track the gait pattern properly propagates instability to the whole system and can cause the robot to fall. To overcome the uncertainties and disturbances, structured specified mixed sensitivityH∞robust controller was proposed to control the quadruped robot legs’ joint angle positions. Before application to the real hardware, the proposed controller was tested on the quadruped robot’s leg planar dynamic model using MATLAB. The proposed controller can control the robot’s legs efficiently even under uncertainties from a set of model parameter variations. The robot was also able to maintain its stability even when it was tested under several terrain disturbances.

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