A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results

Begnini, Mauricio; Bertol, Douglas Wildgrube; Martins, Nardênio Almeida

doi:10.1016/j.conengprac.2017.04.006

Cited by 85 publications

(50 citation statements)

References 38 publications

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“…is the unknown component which need to be estimated. The error dynamics model (18) has the form of (3), then the torque controller is obtained as the following: (20) in which L1 and C1 are positive scalars.…”

Section: Dynamic Controller Designmentioning

confidence: 99%

“…Different working environments of the WMR will have different types of wheel slip depending on many factors, such as an unknown centrifugal force possibly acting on the WMR when it moves in a circular path, an external force acting on the WMR, or a weak frictional force between the slippery floor and the wheels. So the controllers with the assumption of "pure rolling without slip" such as the sliding mode control [2][3][4], the adaptive control [5][6][7][8][9] or the back stepping control [10] cannot satisfy the requirements on the stability as well as the tracking of the system.…”

Section: Introductionmentioning

confidence: 99%

“…By using a fuzzy logic system (FLS) to approximate the model and an adaptive fuzzy observer to estimate the unmeasured velocities, the position errors are minimized and the response of the system is fast. The FLSs are also used for the WMR systems in others researches [15][16][17][18]. The problems of wheel slips are also considered by many researchers.…”

Section: Introductionmentioning

confidence: 99%

“…same simulation is done with the scheme which is presented in[18] for comparison. The parameters of the WMR is as the following: mG = 10 kg, mW = 2 kg, IG = 4 kgm 2 , IW = 0.1 kgm 2 , ID = 0.05 kgm 2 , a = 0.2 m, b = 0.3 m, r = 0.15 m. The control parameters are chosen as: C1 = C2 = 2, L1 = 200, L2 = 300. Case 1: The reference trajectory is oval in shape with the equation:…”

mentioning

confidence: 99%

See 3 more Smart Citations

Robust adaptive controller for wheel mobile robot with disturbances and wheel slips

Ong

Trinh

et al. 2021

IJECE

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In this paper an observer based adaptive control algorithm is built for wheel mobile robot (WMR) with considering the system uncertainties, input disturbances, and wheel slips. Firstly, the model of the kinematic and dynamic loops is shown with presence of the disturbances and system uncertainties. Next, the adaptive controller for nonlinear mismatched disturbance systems based on the disturbances observer is presented in detail. The controller includes two parts, the first one is for the stability purpose and the later is for the disturbances compensation. After that this control scheme is applied for both two loops of the system. In this paper, the stability of the closed system which consists of two control loops and the convergence of the observers is mathematically analysed based on the Lyapunov theory. Moreover, the proposed model does not require the complex calculation so it is easy for the implementation. Finally, the simulation model is built for presented method and the existed one to verify the correctness and the effectiveness of the proposed scheme. The simulation results show that the introduced controller gives the good performances even that the desired trajectory is complicated and the working condition is hard.

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Section: Dynamic Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Robust adaptive controller for wheel mobile robot with disturbances and wheel slips

Ong

Trinh

et al. 2021

IJECE

View full text Add to dashboard Cite

show abstract

“…Function approximation methods have been explored to overcome uncertainties in robust control of nonlinear systems [17][18][19][20][21][22][23][24]. In [25], an adaptive dynamic sliding-mode control system (ADSMCS) with recurrent radial basis function network (RRBFN) for indirect field-orientation control induction motor (IM) drive which guarantees the robustness in the presence of parameter uncertainties and load disturbances has been proposed.…”

Section: Introductionmentioning

confidence: 99%

Design of an adaptive dynamic sliding mode control approach for robotic systems via uncertainty estimators with exponential convergence rate

2020

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In this work, an adaptive dynamic sliding mode control approach is proposed for robotic systems via uncertainty estimators with exponential convergence rate. The uncertainties are estimated using various uncertainty estimators such as the Fourier series expansion, Legendre polynomials and adaptive fuzzy systems. Also, for each uncertainty estimator, the approximation error is compensated. The adaptation laws are derived using a stability analysis. Moreover, the asymptotic convergence of the tracking error and the boundedness of all closed-loop signals are guaranteed. The novelty of this paper is proposing a positive exponential function for the convergence rate of the adaptation rules to prevent from initial high voltages originated from large initial tracking errors. Another novelty of this paper is presenting a robust control term for the truncation error that improves the accuracy of the control system. Analysis of simulations reveals the effectiveness of the proposed method in terms of fast disturbance rejection and negligible tracking error.

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Non‐fragile control for dynamic event‐triggered networked systems with randomly occurring nonlinearities

Liu

Yao

et al. 2022

Math Methods in App Sciences

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This article focuses on the issue of non‐fragile control for a networked control systems (NCSs) with randomly occurring nonlinearities, where an advanced dynamic event‐triggered mechanism (DETM) is introduced. First, an improved DETM transmission strategy for NCSs is proposed. Based on the dynamic error of the system, the improved DETM can adaptively adjust the threshold to control the transmission of signals. The balance of the network bandwidth and control performance is excellently regulated by the adaptive threshold rather than a predetermined constant. Second, by taking the networked‐induced delay, DETM, randomly occurring nonlinearities and controller gain perturbation into consideration, a nonlinear system model is established. Next, sufficient stability conditions that can guarantee the mean‐square asymptotical stability are obtained based on the novel two‐side Lyapunov‐Krasovskii functional (LKF) and second‐order generalized free‐matrix‐based integral inequality (GFMBII), which contains more system information and can provide less conservative results. Finally, two numerical examples are presented to verify the advantages of the proposed method.

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A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results

Cited by 85 publications

References 38 publications

Robust adaptive controller for wheel mobile robot with disturbances and wheel slips

Robust adaptive controller for wheel mobile robot with disturbances and wheel slips

Design of an adaptive dynamic sliding mode control approach for robotic systems via uncertainty estimators with exponential convergence rate

Non‐fragile control for dynamic event‐triggered networked systems with randomly occurring nonlinearities

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