Comparative study between PI and sliding mode controllers for flexible joint manipulator driving by Brushless DC motor

Zouari, Lilia; Abid, Hafedh; Abid, Mohamed

doi:10.1109/sta.2013.6783146

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…Many manipulator robots have flexible joint due to the gear elasticity, the bearing deformation and the shaft windup, etc. [14,15] In this study, we consider one link manipulator robot with revolute joint actuated by brushless direct current motor. The system includes two principal parts which are flexible joint manipulator and brushless direct current motor.…”

Section: Problem Statementmentioning

confidence: 99%

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Sliding mode and PI controllers for uncertain flexible joint manipulator

Zouari

Abid

2015

Int. J. Autom. Comput.

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This paper is dealing with the problem of tracking control for uncertain flexible joint manipulator robots driven by brushless direct current motor (BDCM). Flexibility of joint in the manipulator constitutes one of the most important sources of uncertainties. In order to achieve high performance, all parts of the manipulator including actuator have been modeled. To cancel the tracking error, a hysteresis current controller and speed controllers have been developed. To evaluate the effectiveness of speed controllers, a comparative study between proportional integral (PI) and sliding mode controllers has been performed. Finally, simulation results carried out in the Matlab simulink environment demonstrate the high precision of sliding mode controller compared with PI controller in the presence of uncertainties of joint flexibility.

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Section: Problem Statementmentioning

confidence: 99%

“…where x(t) is the state variable vector, f (x) and g(x) are two continuous bounded nonlinear functions and u is the control vector. The sliding surface can be defined by [27] S = Gx (15) where G is a row vector which describes the dynamics of the sliding surface. It can be chosen as G = [K1 1].…”

Section: Sliding Mode Controllermentioning

confidence: 99%

Sliding mode and PI controllers for uncertain flexible joint manipulator

Zouari

Abid

2015

Int. J. Autom. Comput.

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“…In [13], an adaptive neural network compensator is proposed to improve the control performance of a macro-mini robotic manipulator, and it demonstrates that compared to the mini based on feedback linearization with the PID controller, vibration can be obviously suppressed using the adaptive compensator, and the steady state error is also gradually improved. In [16], for flexible joint manipulator, a comparison between PI and sliding mode control is proposed for the control to improve the performance in the presence of errors in the parameters identification, and it shows the high performances of sliding mode controller by converging the error to zero and guaranteeing the stability of the robot [14]. In [5,6,10], an adaptive backstepping design method is proposed to deal with the system uncertainty for the position tracking control of this robotic manipulator.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Stable Control of Manipulator System Based on Immersion and Invariance

Wang

Jiang

Liu

et al. 2018

Mathematical Modelling and Analysis

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Abstract. This work focused on the manipulator system containing uncertainties, and proposes an immersion and invariance (I&I) control strategy, in order to avoid the damage on the mechanical and the operation object caused by parameter uncertainty. A stable target system with lower dimension than the manipulator system was chosen to design the control law and estimation laws of uncertain parameters. Then finding an invariant and attractive manifold in state space with internal dynamics a copy of the desired closed-loop dynamics. Finally, design a control law that can steer the state of the system sufficiently close to the manifold. The immersion and invariance adaptive control does not rely on certainty equivalence. The whole uncertain parameter estimations are the sum of two terms. One is obtained by an iterative law like the traditional adaptive backstepping method. On the other hand, a nonlinear function is introduced. The role of this additional term makes the parameter estimations more flexible and effective. Lyapunov function is not necessary for the process of designing adaptive controllers. So immersion and invariance can effectively avoid the 'computing expansion' of backstepping method. Compared with the traditional adaptive methods, simulation results show that the proposed immersion and invariance adaptive controller can improve the system performance, including dynamic response, stability and accuracy of parameter estimations.

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A reliable speed controller for suppressing low frequency concussion of electric vehicle

Zhang

Jiang

2018

Microelectronics Reliability

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Comparative study between PI and sliding mode controllers for flexible joint manipulator driving by Brushless DC motor

Cited by 4 publications

References 6 publications

Sliding mode and PI controllers for uncertain flexible joint manipulator

Sliding mode and PI controllers for uncertain flexible joint manipulator

Adaptive Stable Control of Manipulator System Based on Immersion and Invariance

A reliable speed controller for suppressing low frequency concussion of electric vehicle

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