Comparative Study of Some New Hybrid Fuzzy Algorithms for Manipulator Control

Abstract

The robot manipulator is a highly complex system, which is multi-input, multi-output, nonlinear, and time variant. Controlling such a system is a tedious and challenging task. In this paper, some new hybrid fuzzy control algorithms have been proposed for manipulator control. These hybrid fuzzy controllers consist of two parts: a fuzzy controller and a conventional or adaptive controller. The outputs of these controllers are superimposed to produce the final actuation signal based on current position and velocity errors. Simulation is used to test these controllers for different trajectories and for varying manipulator parameters. Various performance indices like the RMS error, steady state error, and maximum error are used for comparison. It is observed that the hybrid controllers perform better than only fuzzy or only conventional/adaptive controllers.

Robust Auto-Intelligent Sliding Accuracy for High Sensitive Surgical Joints

“…This controller is based on online tuning the parameters and caused to improve the trajectory [12,[17][18][19]. The adaptive sliding mode controller is used to estimate the unknown dynamic parameters and external disturbances.…”

“…The dynamic modeling describes the relationship between motion, velocity, and accelerations to force/torque or current/voltage and also it can be used to describe the particular dynamic effects (e.g., inertia, coriolios, centrifugal, and the other parameters) to behavior of system. Spherical motor has nonlinear and uncertain dynamic parameters 3 degrees of freedom (DOF) motor [10][11][12][13][14][15]. The equation of a spherical motor governed by the following equation:…”

Robust Auto-Intelligent Sliding Accuracy for High Sensitive Surgical Joints

“…The dynamic modeling describes the relationship between motion, velocity, and accelerations to force/torque or current/voltage and also it can be used to describe the particular dynamic effects (e.g., inertia, coriolios, centrifugal, and the other parameters) to behavior of system. Spherical motor has nonlinear and uncertain dynamic parameters 3 degrees of freedom (DOF) motor [10][11][12][13][14][15].…”

“…To improve the precision, controller design has the main role. Controller is a device which can sense information from linear or nonlinear system (e.g., surgical joints) to improve the systems performance [11][12][13][14][15][16][17][18][19]. The main targets in designing control systems are stability, good disturbance rejection, and small tracking error [5].…”

Adaptive Fuzzy Computed-Torque Control for Robot Manipulator with Uncertain Dynamics

“…However, because the fuzzy logic rules in the fuzzy control system are determined by some experimental data and designers' experiences rather than the fuzzy adaptive control law, it is very difficult to ensure stability for the general fuzzy control systems with uncertain dynamics. Mohan and Bhanot [19] presented an investigation into three kinds of hybrid fuzzy control algorithms combined with a conventional computed-torque controller. Although performances of a hybrid controller improves appreciably compared to their respective fuzzy or conventional counterparts, the fuzzy controller used in these algorithms is a lookup table-based controller rather than a self-adaptive fuzzy controller, and therefore presents the disadvantage of having to build up the lookup table, which can be a long process.…”