Asymmetric bounded fuzzy adaptive control for uncertain coordinative multiple robot manipulators

Abstract

This work presents a fuzzy adaptive control technology for determining the desired trajectory of collaborative robot manipulators when grasping a general object. While the classical fuzzy logic systems (FLSs) are commonly used to compensate for some unknown nonlinear continuous functions, their approximation accuracies are often limited. To address this issue, a non-zero time-varying parameter is introduced in the input of Mamdani type or Takagi–Sugeno (T–S) type FLSs. This parameter allows for universal approximation, enabling the system to automatically adjust the approximation precision through adaptive rules. The unknown nonlinear continuous functions are represented using a combined form of homogeneous functions, which are then approximated using FLSs. Unlike previous fuzzy adaptive control schemes, this approach overcomes the limitation of a finite universal approximation domain. Additionally, the proposed method can calculate the coefficients of consequents in T–S type FLSs, reducing the computational load of the controller. The effectiveness of the proposed sliding mode surface is demonstrated in ensuring the required tracking performance, with all signals in the closed-loop system being uniformly ultimately bounded (UUB). The efficiency of the control scheme is further demonstrated through various simulation results.