Development of a Power Assist Lifting Device With a Fuzzy PID Speed Regulator

Abstract

This paper introduces the development of a one-degree-of-freedom (1DOF) power assist device that helps to lift objects and facilitate the operator's job. The existing designs were examined for different control approaches and human-robot cooperation intuitiveness. The project involves the mechanical design of the experimental setup and development of advantageous control system. Since a task for the device is highly dependent on the mass of handling object, an adaptive strategy is a major concern of control system design. The controller design is represented by two loops to control admittance and velocity. To reduce the response time of the device, two velocity controllers are designed and compared with the embedded one. The first is a conventional proportional-integral-derivative controller which has shown better performance than the native controller. The second is derived from the first using fuzzy logic for better handling of different manipulation scenarios. The results illustrate that a faster response of the device can be achieved using a fuzzy logic controller due to the nonlinear nature that allows adapting to changes in velocity error and applied load. INDEX TERMS Power assist robot, feedback control, industry, object manipulation, fuzzy logic control.

Machine Learning-Based Cognitive Position and Force Controls for Power-Assisted Human–Robot Collaborative Manipulation

“…We believe that the mentioned dynamic effects and resulting nonlinear forces may have an impact on the system configurations and performance for force controls, especially the force controls of multi-degree-of-freedom systems. However, these types of dynamic effects are not to be so significant for position controls [21,22,28]. All these factors have favored the position control over its counterparts (force controls).…”

“…However, such initiatives were not taken. In addition, we posit that an empirically designed weight-perception-based adaptive control strategy added to the top of the position and force control strategies could be able to adapt the effects generated due to the weight perceptual issues [13,28]. However, such efforts were not attempted in [7].…”

Implementation of Fuzzy Logic Controller Algorithms with MF optimization on FPGA

“…Fuzzy logic control finds applications in various areas, such as speed control, position control, torque control, robotics, automation, and energy efficiency optimization for DC motors. By enabling precise and adaptive control, it effectively addresses non-linearities and varying operating conditions, providing intelligent control strategies for diverse applications [33,29,27].…”

An Optimal Fuzzy Logic-based PI Controller for the Speed Control of an Induction Motor using the V/F Method

“…A Fuzzy Logic-based Controller (FLC) can overcome these disadvantages [8][9][10]. The FLC does not need the model of the plant, can handle non-linearity, it is less sensitive to load disturbances, it produces human logic linguistic rules, and is robust [11][12][13]. Authors in [14] suggested a 3-phase IM speed control technique using constant V/F control.…”