Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator

Sharma, Richa; Rana, K.P.S.; Kumar, Vineet

doi:10.1016/j.eswa.2013.12.030

Cited by 209 publications

(80 citation statements)

References 37 publications

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“…(1) The kinematic uncertainties of the manipulator are taken into consideration without the prior knowledge of system. (2) No dynamic models of the robot manipulator system are required. (3) The adaptive fuzzy logic scheme is implemented as the third element to compensate the TDE error and eliminate the undesired chattering in NTSM.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

See 1 more Smart Citation

Task Space Trajectory Tracking Control of Robot Manipulators with Uncertain Kinematics and Dynamics

Liang

Wan

Zhang

2017

Mathematical Problems in Engineering

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To improve the tracking precision of robot manipulators' end-effector with uncertain kinematics and dynamics in the task space, a new control method is proposed. The controller is based on time delay estimation and combines with the nonsingular terminal sliding mode (NTSM) and adaptive fuzzy logic control scheme. Kinematic parameters are not exactly required with the consideration of kinematic uncertainties in the controller. No dynamic models or numerous parameters of the robot manipulator system are required with the use of TDE. Thus, the controller is simple structure and suitable for practical applications. Furthermore, errors caused by time delay estimation are compensated by the adaptive fuzzy nonsingular terminal sliding mode scheme. The simulation is performed on a 2-DOF robot manipulator with three cases in the task space. The results show that the proposed controller provides faster convergence rate and higher tracking precision than TDE based NTSM and improved TDE based NTSM controller.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

“…Robot manipulators play an important role in the industry automation field in recent years [1][2][3]. One of the irreplaceable capabilities of robot manipulations is the high accuracy and high-speed performance of trajectory tracking.…”

Section: Introductionmentioning

confidence: 99%

Task Space Trajectory Tracking Control of Robot Manipulators with Uncertain Kinematics and Dynamics

Liang

Wan

Zhang

2017

Mathematical Problems in Engineering

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“…In [1] the authors proposed a new approach for robust control by fractionalizing an integer order integrator in the classical PID control scheme and they use the Sub-optimal Approximation of fractional order transfer function to design the parameters of PID controller .In [2], the authors designed a new tuning rules for the tuning parameters of FOPID based on ZieglerNichols (Z-N) rule, A new tuning method for designing fractional order PID controllers based on radial basis function (RBF) neural networks was proposed in [3]. Sharma et al [4] proposed a Fractional Order Fuzzy Proportional Integral Derivative (FOFPID) controller for a two-link planar rigid robotic manipulator for trajectory tracking problem. For tuning of parameters of all the controllers, Cuckoo Search Algorithm (CSA) optimization technique was used.…”

Section: Introductionmentioning

confidence: 99%

Speed Control of DC Motor Using PID and FOPID Controllers Based on Differential Evolution and PSO

Idir¹,

Kidouche²,

Bensafia³

et al. 2018

IJIES

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DC motors are widely used in industrial application for its different advantage such us high efficiency, low costs and flexibilities. For controlling the speed of DC motor, conventional controller PI and PID were the most widely used controllers. But due to empirically selected parameters , , and limitation of convention PID controller to achieve ideal control effect for higher order systems, a Fractional order Proportional-IntegralDerivative PID (FOPID) based on optimization techniques was proposed in this paper. The aim of this paper is to study the tuning of a FOPID controller using intelligent soft computing techniques such as Differential Evolution (DE) and Particle Swarm Optimization (PSO) for designing fractional order PID controller. The parameters of FOPID controller are determined by minimizing the Integral Time Absolute Error (ITAE) between the output of reference model and the plant. The performance of DE and PSO were compared with several simulation experiments. The simulation results show that the DE-based FOPID controller tuning approach provides improved performance for the setpoint tracking, error minimization, and measurement noise attenuation.

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“…Input to the fuzzy inference came from the control error and the rate of control error while 49 fuzzy rules were designed exclusively for each gain. The same approach was used by [19] for trajectory control of robotic manipulator. Recent research had reported to implement fuzzy FOPID on distillation column [20], while others had demonstrated different PID structure with fuzzy FOPID [21][22].…”

mentioning

confidence: 99%

Steam temperature control of essential oil extraction system using Fuzzy-Fopi controller

Tajjudin¹,

Ishak²,

Rahiman³

et al. 2018

J. Fundam and Appl Sci.

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This research proposed a closed fractional-order PI (FOPI) controller to overcome the problem. The controller will regulate the steam temperature at a desired level to protect the oil from excessive heat. Self capability of fuzzy rules was found to facilitate the tuning using only information about output error and rate of output error. The proposed controller was found to be more in terms of energy consumption and produce better response compared to self Essential oil quality assessment was also performed for citronella oil samples that extracted at 85ºC and 100ºC (uncontrolled). Significant improve the sample extracted at 85ºC based on physical and chemical evaluations using refractive index measurement and GC-MS analysis. his research proposed a closed-loop temperature control using a self order PI (FOPI) controller to overcome the problem. The controller will regulate temperature at a desired level to protect the oil from excessive heat. Self capability of fuzzy rules was found to facilitate the tuning using only information about output error and rate of output error. The proposed controller was found to be more in terms of energy consumption and produce better response compared to self Essential oil quality assessment was also performed for citronella oil samples that ºC (uncontrolled). Significant improvement had been observed in the sample extracted at 85ºC based on physical and chemical evaluations using refractive MS analysis. fuzzy control;

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Performance analysis of fractional order fuzzy PID controllers applied to a robotic manipulator

Cited by 209 publications

References 37 publications

Task Space Trajectory Tracking Control of Robot Manipulators with Uncertain Kinematics and Dynamics

Task Space Trajectory Tracking Control of Robot Manipulators with Uncertain Kinematics and Dynamics

Speed Control of DC Motor Using PID and FOPID Controllers Based on Differential Evolution and PSO

Steam temperature control of essential oil extraction system using Fuzzy-Fopi controller

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