Robust control strategy for electrically driven robot manipulators: adaptive fuzzy sliding mode

Abstract

In this study, a sliding mode controller is designed to control the position tracking of robot manipulator. The proposed control has global asymptotical stability in the presence of structured uncertainties, un-structured uncertainties and un-modelled dynamics of the robot manipulator as well as in motors dynamics. The proposed control structure is designed in such a way that initially, by using inverse dynamic method, it reduces the uncertainties bound and finally, sliding mode control eliminates the influence of the remaining uncertainties in closed-loop system stability. Further, in control input for eliminating undesirable chattering phenomena using the fuzzy logic, an adaptive fuzzy approximator is designed in such way that approximates the uncertainty bounds. Mathematical proof shows that the adaptive fuzzy sliding mode control of a closed-loop system has global asymptotical stability. Since the number of existing fuzzy rules are low in adaptive fuzzy approximator rules base and in single input-single output form, so control input computational load is very low and this order makes the proposed control of practical implementation possible. To evaluate the performance of the proposed controller, a case study on a robot manipulator with two degrees of freedom is implemented. Simulation results show the desired performance of the proposed controller.

Optimum design of a novel redundantly actuated parallel manipulator with multiple actuation modes for high kinematic and dynamic performance

“…It is noted that the friction compensation can be considered into the controller design for a comprehensive APD control [15,16]. Furthermore, some intelligent control methods [46][47][48] can be employed to guarantee the stability of the closed-loop system in the case of uncertainties.…”

Adaptive fuzzy backstepping output constraint control of flexible manipulator with actuator saturation

“…Fateh and Souzanchikashani [2] put forward an indirect adaptive fuzzy control for electrically driven flexible-joint robot manipulators in which a novel estimation technique is introduced to estimate the uncertainty. Soltanpour et al [3] proposed an adaptive sliding mode control method to design the position tracking control of robot manipulator. Yang et al [4] proposed an adaptive backstepping control design method for a flexible robot manipulator system by utilizing Lyapunov function.…”

“…The proposed output feedback control scheme can be used to control a single-link flexible manipulator system, which does not require that the speed of the generator rotor is measured directly. Note that the previous references [1][2][3][4][5][6] assumed that all the states in the systems are measurable. Thus, they cannot be used for dealing with the states immeasurable of the singlelink flexible manipulator system.…”

“…To finish the tasks more accurately, modeling and control for a flexible manipulator have been received much attention recently. Some approaches are proposed for the control problem of flexible-joint robots [1][2][3][4]. Cheng [1] proposed an adaptive neural-fuzzy control scheme for a class of flexible manipulator with variable dynamic payload and achieved the tracking control.…”

Robot Trajectory Tracking Control Based on Look-up Table Method

“…track a given geometry path. Based on adaptive control [6][7][8][9], sliding mode control [10][11][12][13], back-stepping design [14][15], PID control, fuzzy control and high gain control, many trajectory tracking controller were obtained for mobile robot [16][17][18][19]. A smooth linear or non-linear function is often used to describe the desired trajectory when presenting and analyzing problems.…”