Adaptive Fuzzy Sliding Mode Control for a 3-DOF Parallel Manipulator with Parameters Uncertainties

Abstract

Parallel manipulators possess the advantages of being compact structure, high stiffness, stability and high accuracy, so such parallel manipulators have been widely employed in application fields as diverse as parallel kinematic machine, motion simulator platform, medical rehabilitation device, and so on. Due to the complexity of the closed-loop structural system, an accurate dynamic model is very difficult to be derived in the absence of some uncertainties parameters and external disturbances. In order to improve the trajectory tracking accuracy with time-varying and nonlinear parameters, this paper addresses the design and implement of adaptive fuzzy sliding mode control (AFSMC) for a three-degree-of-freedom (DOF) parallel manipulator, where internal force term can be linearly separated into a regression matrix and a parameter vector that contains the estimated errors. Furthermore, fuzzy inference unit is utilized to modify the gain parameters in real-time by using the state feedback from the task space and the adaptive law is performed to update uncertainties in dynamic parameters. The proposed controller is deduced in the sense of Lyapunov theory to guarantee the stability while improving the trajectory tracking performance. Finally, simulation experiment results demonstrate that the proposed control method is insensitive to uncertainties and disturbances and permits to decrease the requirement for the bound of these uncertainties, which validate the effectiveness of the developed control method and exhibit good trajectory tracking performance compared with sliding mode control (SMC) and fuzzy sliding model control (FSMC).

A Gradient-Based Recurrent Neural Network for Visual Servoing of Robot Manipulators with Acceleration Command

“…Owing to the derivative process that GRNN (26) originates from the error function ( 17), the gradient descent formula is designed to reduce the image error, thus ultimately achieving equality constraint (13). In the next place, the output control command is established at the acceleration level, which corresponds to the acceleration-level kinematics formula (12).…”

“…In current years, the kinematic control of redundant robots has become a research hotspot, thus drawing the attention of abundant scholars to expand their applications [12][13][14][15][16]. Zhang and Zhang present a minimum-velocity-norm (MVN) scheme for redundancy resolution of the redundant manipulators, which retains the robot joints within safe bounds [17].…”

Modelling an Industrial Robot and Its Impact on Productivity

“…To efficiently plan the motion is vital to compute the system dynamics. However, due to the parameter uncertainties and the highly nonlinear dynamic parameters, there is a difference between the desired motion and the real motion obtained with these algorithms [19]. The discrepancies range from time-varying loads, parameter variations, errors in mounting the robot arms, malfunctioning of actuator forces or torques, overload or excess voltage, noise and disturbances.…”

Fixed-Time Bounded H Infinity Tracking Control of a Single-Joint Manipulator System with Input Saturation

“…It should be noted that there are many research methods for robotic arms under certain circumstances. The most widely used approaches are to combine the backstepping control strategy with adaptive control [10][11][12][13][14]. Yang [10] designed an adaptive neural finite-time controller.…”

“…An adaptive H infinity fault-tolerant controller was proposed in [12]. [13] and [14] combined manipulator systems and adaptive fuzzy logic systems to design the controllers. The other tracking control research was based on robust control method [15,16].…”