Integrated Mechanism Design and Control for Completely Restrained Hybrid-Driven Based Cable Parallel Manipulators

Dynamic optimum design of a 3UPS-PRU parallel robot

This article deals with the methodology of the dynamic optimum design of the one translational and three rotational degrees of freedom parallel robots while considering the rigid-body dynamic property. The dynamic optimum design of the 3UPS-PRU (underlined P denotes an active prismatic joint driven by a servomotor) parallel robot is presented while considering the constraints on the installation dimension, joint rotation angle, and the interference. The maximum driving torque and the maximum driving power of the actuating joints are taken as the objective functions in the dynamic optimum design, respectively. The physical meanings of the objective functions are the maximum driving torque and the maximum driving power of the actuating joints when the moving platform translates along the z-axis in the maximum linear acceleration amax, rotates about an arbitrary axis in the maximum angular acceleration αmax, translates along the z-axis in the maximum linear velocity vmax, and rotates about an arbitrary axis in the maximum angular velocity ωmax at the same time. The object of the dynamic optimum design is to minimize the maximum driving torque or the maximum driving power by employing worst case criterion. In the predefined design task, the results of the dynamic optimum design of the 3UPS-PRU parallel robot are the same when taking the maximum driving torque and the maximum driving power as the objective functions. The phenomenon can be verified by the fact that the distributions of the maximum driving torque and the maximum driving power are very similar to each other. The robot dimension has also been taken into account in the dynamic optimum design of the 3UPS-PRU parallel robot due to the consideration of the building cost and the miniaturization. The example of the dynamic optimum design of the 3UPS-PRU parallel robot is presented in the simulation. The conclusions are provided at the end of the article.

Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot

A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm.