Controller Design and Trajectory Tracking of a Two-Link Robotic Orthosis via Sinusoidal-Input Describing Function Model

Chin, Kar Mun; Teh, Sze-Hong; Ho, Jee-Hou; Ng, Hoon Kiat

doi:10.18178/ijmerr.8.6.845-851

Cited by 2 publications

(2 citation statements)

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“…This newly generated position is selected based on the fitness (RMS Error) & the loudness A t i of the corresponding bat. The pulse rate r t i and loudness A t i of each bat is updated using equations (8,9) only if this new bat is accepted.…”

Section: Bat Algorithm (Bat)mentioning

confidence: 99%

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Meta-Heuristics Based Inverse Kinematics of Robot Manipulator’s Path Tracking Capability Under Joint Limits

Kanagaraj

Masthan

2022

mendel

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In robot-assisted manufacturing or assembly, following a predefined path became a critical aspect. In general, inverse kinematics offers the solution to control the movement of manipulator while following the trajectory. The main problem with the inverse kinematics approach is that inverse kinematics are computationally complex. For a redundant manipulator, this complexity is further increased. Instead of employing inverse kinematics, the complexity can be reduced by using a heuristic algorithm. Therefore, a heuristic-based approach can be used to solve the inverse kinematics of the robot manipulator end effector, guaranteeing that the desired paths are accurately followed. This paper compares the performance of four such heuristic-based approaches to solving the inverse kinematics problem. They are Bat Algorithm (BAT), Gravitational Search Algorithm (GSA), Particle Swarm Optimization (PSO), and Whale Optimization Algorithm (WOA). The performance of these algorithms is evaluated based on their ability to accurately follow a predefined trajectory. Extensive simulations show that BAT and GSA outperform PSO and WOA in all aspects considered in this work related to inverse kinematic problems.

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Section: Bat Algorithm (Bat)mentioning

confidence: 99%

“…To name a few, Discrete-Time Nonlinear Optimization control [21], Sliding mode controller [30], adaptive control [49]. A sinusoidal-input describing function model along was created along with a controller for a twolink robot manipulator in [9]. A trajectory algorithm using artificial neural network and Kalman filter was proposed by [27].…”

Section: Introductionmentioning

confidence: 99%