Normal and tangent force neuro-fuzzy control of a soft-tip robot with unknown kinematics

García-Rodríguez, R.; Parra-Vega, Vicente

doi:10.1016/j.engappai.2017.07.013

Cited by 7 publications

(1 citation statement)

References 19 publications

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“…In order to increase the efficiency of controller tuning, advanced methods are used, using, for example, genetic algorithms [36] or particle swarm optimisation [37]. When it comes to hybrid position-force control of robots using neuro-fuzzy systems, the basics of the theory are included in the article [38], while more advanced issues taking into account the uncertainty of the environment or robot kinematics are described in papers [12,39,40]. Among the cited works, only [39] presents the results of the experimental verification of the solution.…”

Section: Literature Reviewmentioning

confidence: 99%

Neural Control of a Robotic Manipulator in Contact with a Flexible and Uncertain Environment

Gierlak

2023

Acta Mechanica Et Automatica

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This article presents the synthesis of a neural motion control system of a robot caused by disturbances of constraints limiting the movement, which are the result of flexibility and disturbances of the contact surface. A synthesis of the control law is presented, in which the knowledge of the robot’s dynamics and the parameters of a susceptible environment is not required. Moreover, the stability of the system is guaranteed in the case of an inaccurately known surface of the environment. This was achieved by introducing an additional module to the control law in directions normal to the surface of the environment. This additional term can be interpreted as the virtual viscotic resistance and spring force acting on the robot. This approach ensured the self-regulation of the robot’s interaction force with the compliant environment, limiting the impact of the geometrical inaccuracy of the environment.

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