Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors

Yongqing Fan,Keyi Xing,Xiangkui Jiang

doi:10.1155/2018/5468090

Yongqing Fan, Keyi Xing + Show 1 more

Open Access

https://doi.org/10.1155/2018/5468090

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Abstract

A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators’ system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a reference model dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example.

Highlights

Technologies of learning and adaptation in complex dynamical systems have been become an indispensable part of modern high-tech and attracted the attention in different range of engineering fields
Many technologies about dynamical complex systems can be described as learning human-like skills, such as making the states following a given reference model in [4]; the robot slave arm is employed to drive the adaptation algorithms according to human tutors behavior [5]
From the viewpoint of mathematics, ordinary differential equations (ODE) can be represented between the master and slave of robot systems, so the synchronization between them is closely similar to observer problem [10, 11], which means that some mathematical methods in control theory may be employed to solve the problem of synchronization for master-slave robot systems

Summary

Introduction

Technologies of learning and adaptation in complex dynamical systems have been become an indispensable part of modern high-tech and attracted the attention in different range of engineering fields. It is noteworthy to exploit another design adaptation algorithm that can be utilized in the FLSs with linear combinatorial parameters or a great variety of the outputs forms of FLSs. In order to achieve this purpose, we consider the approximation accuracies of FLSs, utilized to be parameter estimated online instead of online estimation of the linear combination coefficients or the ideal norm of weighted vectors. In order to achieve this purpose, we consider the approximation accuracies of FLSs, utilized to be parameter estimated online instead of online estimation of the linear combination coefficients or the ideal norm of weighted vectors The advantage of this design is that the adaptive online learning laws only focus on the approximation accuracies. Simulation example is performed to test the designed controller, and conclusion is given in the end

System Description and Assumptions

Description of Fuzzy Logic Systems

Fuzzy Adaptation Algorithms Control Design

Simulation Example

Conclusions