The Hybrid Position/Force Walking Robot Control Using Extenics Theory and Neutrosophic Logic Decision

Sensors (Basel). 2022 May 11;22(10):3663. doi: 10.3390/s22103663.

Abstract

This paper presents a hybrid force/position control. We developed it for a hexapod walking robot that combines multiple bipedal robots to increase its load. The control method integrated Extenics theory with neutrosophic logic to obtain a two-stage decision-making algorithm. The first stage was an offline qualitative decision-applying Extenics theory, and the second was a real-time decision process using neutrosophic logic and DSmT theory. The two-stage algorithm separated the control phases into a kinematic control method that used a PID regulator and a dynamic control method developed with the help of sliding mode control (SMC). By integrating both control methods separated by a dynamic switching algorithm, we obtained a hybrid force/position control that took advantage of both kinematic and dynamic control properties to drive a mobile walking robot. The experimental and predicted results were in good agreement. They indicated that the proposed hybrid control is efficient in using the two-stage decision algorithm to drive the hexapod robot motors using kinematic and dynamic control methods. The experiment presents the robot's foot positioning error while walking. The results show how the switching method alters the system precision during the pendulum phase compared to the weight support phase, which can better compensate for the robot's dynamic parameters. The proposed switching algorithm directly influences the overall control precision, while we aimed to obtain a fast switch with a lower impact on the control parameters. The results show the error on all axes and break it down into walking stages to better understand the control behavior and precision.

Keywords: decision method; extension set; hybrid position/force control; neutrosophic logic; sliding mode control.

MeSH terms

  • Algorithms
  • Biomechanical Phenomena
  • Logic
  • Robotics* / methods
  • Walking