24 research outputs found

    Adaptive Fuzzy Control of Puma Robot Manipulator in Task Space with Unknown Dynamic and Uncertain Kinematic

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    A In this paper, an adaptive direct fuzzy control system is presented to control the robot manipulator in task space. It is assumed that robot system has unknown dynamic and uncertain kinematic. The control system and adaption mechanism are firstly designed for joint space tracking. Then by using inverse Jacobian strategy, it is generalized for task space. After that, to overcome the problem of Jacobian matrix uncertainty, an improved adaptive control system is designed. All the design steps are illustrated by simulations

    Design of PID, FLC and Sliding Mode Controller for 2-DOF Robotic Manipulator: A Comparative Study

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    Controlling the manipulators in a precise manner is a challenging task. To overcome this difficulty around the world, many researchers have developed various control algorithms but are not providing optimal results. To obtain the optimal results in the current research the authors designed a proportional, integral, and derivative (PID) controller, fuzzy logic controller (FLC), and sliding mode controller (SMC) for a 2-DOF manipulator. The concept of forward and inverse kinematics was initially solved after assigning the D-H parameters for each joint. The purpose of forward or direct kinematics is to obtain the position and orientation of the end effector. Further, the concept of inverse kinematics is used to estimate the joint angles. Later on, the Lagrange-Euler formulation was used to calculate the dynamics of the 2-DOF manipulator, which is required to estimate the torque required for each joint of the robotics arm. The main goal of this research problem is to optimize the angular error between the two successive events. Finally, the developed algorithm is compared with the existing algorithms such as PID and Fuzzy logic controller
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