Adaptive Fuzzy Output Feedback Control of a Nonholonomic Wheeled Mobile Robot

Peng, Shuying; Shi, Wuxi

doi:10.1109/access.2018.2862163

Cited by 44 publications

(31 citation statements)

References 44 publications

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“…e x x  is the tracking error, C is the positive constant vector. Substituting (14) into (13) then the following result is obtained: e Ce (15) Because C is positive then the closed loop is asymptotically stable.…”

Section: Adaptive Controller Design For Nonlinear Mismatched Disturbamentioning

confidence: 99%

“…A robust controller based on disturbance observer for trajectory tracking of wheeled mobile robots presented in [13] is used to track the trajectory in the presence of disturbance and unknown parameters. In [14], the trajectory tracking problem for WMR under conditions of system uncertainties and external disturbances is addressed. 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.…”

Section: Introductionmentioning

confidence: 99%

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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: Adaptive Controller Design For Nonlinear Mismatched Disturbamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

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“…In [16] a fuzzy PD controller for a dynamic model of nonholonomic mobile manipulator in order to treat the trajectory tracking control and to eliminate the effect of external force on the end-effector is proposed. Concerning the robustness of the Fuzzy approach, the paper in [17] addresses the output feedback trajectory tracking problem for a nonholonomic wheeled mobile robot in the presence of parameter uncertainties, external disturbances, and a lack of velocity measurements. A combination between a heuristic Fuzzy and PID controller is also designed in [18] to move the robot upward or downward the inclined plane and approach the target point.…”

Section: Fuzzy Control Algorithm Integrated With a Pd Controllermentioning

confidence: 99%

Using Fuzzy PD Controllers for Soft Motions in a Car-like Robot

Mercorelli¹

2018

Adv. sci. technol. eng. syst. j.

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This paper deals with the control problem for nonholonomic wheeled mobile robots moving on the plane, and in particular, the use of a Fuzzy controller technique for achieving a given motion task which consists of following a rectilinear trajectory until an obstacle occurs on the path. After a background part, in which the fundamental knowledge of Fuzzy control is considered, the problem of the avoidance of an obstacle is taken into consideration. When an obstacle occurs on the path, the drive assistant provides for its avoidance calculating the minimal distance from which the avoidance maneuver starts. Conditions on the parameters of a PD controller are calculated using a Fuzzy based approach. An observer is designed to obtain unmeasurable states to be used in the control loop. In the Appendix of this paper a formal demonstration of a Proposition is proven in which the convergence of the system state estimation of the observer is shown. Simulations considering a real transporter vehicle for a storage service are shown.

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“…The DDWMR has some different forms, such as a 2wheel, a 3-wheel, or a 4-wheel type. We can find the 2-wheel type in [13], the 3-wheel type in [5], [7], [10], [11], [18], [19], [20], [23], and the 4-wheel type in [15], [17]. The 3wheel type is the most popular form which comprises of two fixed powered wheels mounted on both left and right side of the robot platform and one passive castor wheel used for balance and stability.…”

Section: Introductionmentioning

confidence: 99%

“…However, the path tracking is more important because its accuracy directly affects the robot operability. Many authors have researched and published various control algorithms of path tracking for the DDWMR, such as the adaptive output feedback control [2], the input-output feedback linearization method [4], the two-step feedback linearization control [3], the backstepping-based control [5], the PID control [6], the Lyapunov function-based control [8], [9], the adaptive and sliding mode control [7], [10], [11], [18], the neural-network-based control [19], and the robust adaptive-based control [21]. All of the above studies refer only to continuous or smooth curves, whereas the energy consumption of the robot is not mentioned.…”

Section: Introductionmentioning

confidence: 99%

Energy Comparison of Controllers Used for a Differential Drive Wheeled Mobile Robot

et al. 2020

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In order to select the best controller for a Differential Drive Wheeled Mobile Robot (DDWMR), an energy consumption comparison relating to tracking accuracy is used as a very strict criterion. Therefore, this paper reviews some well-known controllers designed for the DDWMR. Furthermore, there are presented several experiments with the extensible open-source code programmed in Python. Such an extensible open-source code presentation could serve as a tool for simulating, comparing, and evaluating a set of different control algorithms. The kinematic and dynamic models of the DDWMR and control algorithms are implemented in this open-source code to determine a travel time, a distance between the robot's position and a given path, a linear velocity, an angular velocity, a travel path length, and a total kinetic energy loss of the DDWMR. These simulation results are used to compare and evaluate the given control algorithms. Moreover, the simulation results also enable to answer the question of whether a significant increase in energy consumption is worth shortening the travel path by just a bit. Finally, this paper includes a direct link to the stored experiments which are runnable and could serve as a proof. Besides, users can also easily supplement with other controllers and different paths to evaluate robot tracking control algorithms.

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Adaptive Fuzzy Output Feedback Control of a Nonholonomic Wheeled Mobile Robot

Cited by 44 publications

References 44 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

Using Fuzzy PD Controllers for Soft Motions in a Car-like Robot

Energy Comparison of Controllers Used for a Differential Drive Wheeled Mobile Robot

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