Design of two-layered fractional order fuzzy logic controllers applied to robotic manipulator with variable payload

Sharma, Richa; Gaur, Prerna; Mittal, A.P.

doi:10.1016/j.asoc.2016.05.043

Cited by 52 publications

(26 citation statements)

References 42 publications

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“…. ; then system (17) is globally ( − ) stable. That is, the drive-response-based coupled systems (5) and 7can reach global ( − ) synchronization.…”

Section: Resultsmentioning

confidence: 99%

“…Fractional-order calculus has gained an increasing attention in physical systems and engineering systems. Fractionalorder dynamic systems containing fractional derivatives and integrals have been investigated in the field of control systems [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Investigating analytical skills in fractionalorder dynamic systems is one important theme.…”

Section: Introductionmentioning

confidence: 99%

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Centralized Data-Sampling Approach for GlobalOt-αSynchronization of Fractional-Order Neural Networks with Time Delays

Zhang¹

2017

Discrete Dynamics in Nature and Society

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In this paper, the globalO(t-α)synchronization problem is investigated for a class of fractional-order neural networks with time delays. Taking into account both better control performance and energy saving, we make the first attempt to introduce centralized data-sampling approach to characterize theO(t-α)synchronization design strategy. A sufficient criterion is given under which the drive-response-based coupled neural networks can achieve globalO(t-α)synchronization. It is worth noting that, by using centralized data-sampling principle, fractional-order Lyapunov-like technique, and fractional-order Leibniz rule, the designed controller performs very well. Two numerical examples are presented to illustrate the efficiency of the proposed centralized data-sampling scheme.

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“…. ; then system (17) is globally ( − ) stable. That is, the drive-response-based coupled systems (5) and 7can reach global ( − ) synchronization.…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Centralized Data-Sampling Approach for GlobalOt-αSynchronization of Fractional-Order Neural Networks with Time Delays

Zhang¹

2017

Discrete Dynamics in Nature and Society

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“…where Equations (9) to (16) represent the main model of the proposed robotic manipulator. Equations (9) and (10) demonstrate the position of each robotic link. Equations (11) and (12) characterize the velocity of each robotic link.…”

Section: The Robotic Manipulator Modelingmentioning

confidence: 99%

“…In literature, various control strategies are utilized for the robotic manipulator such as the proportional integral derivative (PID) controller, [3][4][5][6] the fractional-order PID controller, [7][8][9] the fuzzy logic controller, 10,11 and the neural network. 12 Among these controllers, the model predictive control (MPC) is approved as an effective control technique for linear and nonlinear systems in complicated and simple industrial applications.…”

Section: Introductionmentioning

confidence: 99%

Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm

Elsisi

2020

Int J Intell Syst

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The controller design for the robotic manipulator faces different challenges such as the system's nonlinearities and the uncertainties of the parameters. Furthermore, the tracking of different linear and nonlinear trajectories represents a vital role by the manipulator. This paper suggests an optimal design for the nonlinear model predictive control (NLMPC) based on a new improved intelligent technique and it is named modified multitracker optimization algorithm (MMTOA). The proposed modification of the MTOA is carried out based on opposition‐based learning (OBL) and quasi OBL approaches. This modification improves the exploration behavior of the MTOA to prevent it from becoming trapped in a local optimum. The proposed method is applied on the robotic manipulator to track different linear and nonlinear trajectories. The NLMPC parameters are tuned by the MMTOA rather than the trial and error method of the designer. The proposed NLMPC based on MMTOA is compared with the original MTOA, genetic algorithm, and cuckoo search algorithm in literature. The superiority and effectiveness of the proposed controller are confirmed to track different linear and nonlinear trajectories. Furthermore, the robustness of the proposed method is emphasized against the uncertainties of the parameters.

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“…To cope with these issues, some techniques have been proposed to improve tracking performance. R. Sharma et al came up with two-layer fraction order fuzzy logic controller [31][32][33] and mixed locally recurrent neural network [33] with the Cuckoo search algorithm (CSA). By combining with optimization technique to determine the optimal control parameters with the payload, the results indicated that the tracking performance is improved under the presence of the payload.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Backstepping Sliding Mode Control for a 3-DOF Hydraulic Manipulator with Nonlinear Disturbance Observer for Large Payload Variation

Truong

Tran

et al. 2019

Applied Sciences

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The paper proposes an adaptive fuzzy position control for a 3-DOF hydraulic manipulator with large payload variation. The hydraulic manipulator uses electrohydraulic actuators as primary torque generators to enhance carrying payload of the manipulator. The proposed control combines backstepping sliding mode control, fuzzy logic system (FLS), and a nonlinear disturbance observer. The backstepping sliding mode control includes a sliding mode control for manipulator dynamics and a PI control for actuator dynamics. The fuzzy logic system is utilized to adjust the control gain and robust gain of the sliding mode control (SMC) based on the output of the nonlinear disturbance observer to compensate the payload. The Lyapunov approach and backstepping technique are used to prove the stability and robustness of the whole system. Some simulations are implemented, and the results are compared to other controllers to exhibit the effectiveness of the proposed control.

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Design of two-layered fractional order fuzzy logic controllers applied to robotic manipulator with variable payload

Cited by 52 publications

References 42 publications

Centralized Data-Sampling Approach for GlobalOt-αSynchronization of Fractional-Order Neural Networks with Time Delays

Centralized Data-Sampling Approach for GlobalOt-αSynchronization of Fractional-Order Neural Networks with Time Delays

Optimal design of nonlinear model predictive controller based on new modified multitracker optimization algorithm

Adaptive Fuzzy Backstepping Sliding Mode Control for a 3-DOF Hydraulic Manipulator with Nonlinear Disturbance Observer for Large Payload Variation

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