Observer-Based Adaptive Fuzzy Sliding Mode Control of Uncertain Multiple-Input Multiple-Output Nonlinear Systems

Abstract

In this paper, the proposed observer-based robust adaptive fuzzy sliding mode control scheme can deal with the problem of robust stability for a class of uncertain multi-input multi-output (MIMO) nonlinear systems whose states are not available. The fuzzy basis function is used to approximate an unknown nonlinear function according to some adaptive laws, and then the state observer is designed for estimating the states of the plant, upon which a adaptive fuzzy sliding mode controller is investigated. Based on the Lyapunov stability theorem and the theory of variable structure control, the proposed robust adaptive fuzzy sliding mode control scheme can guarantee the robust stability of the whole closed-loop system and obtain good tracking performance. Finally, the simulation results are carried out on a two-link robot manipulator to illustrate the performance of the proposed approach.

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]. The equation of a spherical motor governed by the following equation:…”

Methodologies of Chattering Attenuation in Sliding Mode Controller

“…̇ ̈ , and trucking error vector is defined by [6]: ̃ ̃ ̃ (11) A time-varying sliding surface in the state space is given by [6][7][8][9]: ̃ (12) where λ is the positive constant. To further penalize tracking error, integral part can be used in sliding surface part as follows [6]:…”

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].…”

“…Based on above discussion, the performance of fuzzy computed torque controller increase in presence of uncertainty and external disturbances. Vivas and Mosquera [15] research about comparative study between predictive functional controller and computed torque controller in uncertain environment. Based on this research, in presence of uncertainty predictive strategy gives better result as a performance however these two methods have about the same performance in certain environment.…”

“…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].…”