Switching algorithm for robust configuration control of a wheeled vehicle

Widyotriatmo, Augie; Hong, Keum–Shik

doi:10.1016/j.conengprac.2011.11.007

Cited by 22 publications

(23 citation statements)

References 37 publications

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“…To the present work, differing from that of [12], assumes only that the movement of the vehicle is in the forward direction.. O and the moment of inertia of the rear wheel with respect to the normal axis of the flat surface, respectively; further, let r I and f I be the mass moments of inertia of the rear and front wheels, respectively, r r and f r be the radii of the rear and front wheels, r ϕ and f ϕ be the rear and front rotation angle of the read and front wheels,…”

Section: Introductionmentioning

confidence: 57%

“…In this work, uncertainty was not taken into consideration, though [12] subsequently did so, thereby improving the control scheme.…”

Section: Introductionmentioning

confidence: 98%

“…Other studies have employed navigation functions [9]- [12] In [9]- [11], a novel navigation function for a nonholonomic rear-steered wheeled vehicle was proposed. In this work, uncertainty was not taken into consideration, though [12] subsequently did so, thereby improving the control scheme.…”

Section: Introductionmentioning

confidence: 99%

“…By choosing the same ) ( p S as that in [12], the first and second time-derivations of p are given as…”

Section: Introductionmentioning

confidence: 99%

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Sliding-mode control of a wheeled vehicle using neural network estimator

Pamosoaji

Hong

Cát³

2013

2013 9th Asian Control Conference (ASCC)

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A motion control problem of a rear-steered wheeled vehicle in consideration of the presence of uncertainties is addressed. Modeling error and additional uncertainties are taken into consideration. A sliding mode controller combining with a radial basis function neural network (RBFNN)-based estimator is proposed. The stability of the proposed control method is proven using Lyapunov stability analysis. Simulation results demonstrating the performance of the proposed control law are presented. It can be concluded that the driving velocity and steering angle performances of the proposed controllers are reasonably acceptable.

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Section: Introductionmentioning

confidence: 57%

“…In this work, uncertainty was not taken into consideration, though [12] subsequently did so, thereby improving the control scheme.…”

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

“…By choosing the same ) ( p S as that in [12], the first and second time-derivations of p are given as…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Sliding-mode control of a wheeled vehicle using neural network estimator

Pamosoaji

Hong

Cát³

2013

2013 9th Asian Control Conference (ASCC)

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“…The position-based control needs more advanced sensing capability and lesser interactions inter-agents comparing to the two other methods. The advancement of position sensors have been shown including global positioning system (GPS) [1], inertial navigation system-(INS) [4], vision- [19], [20], laser-based localization [21], [22], and many more. This paper focuses on the position-based formation control.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Leader-Follower Formation Control of a Team of Nonholonomic Mobile Robots

Widyotriatmo

Joelianto

Prasdianto

et al. 2017

INT J COMPUT COMMUN

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A control method for a team of multiple mobile robots performing leaderfollower formation by implementing computing, communication, and control technology is considered. The strategy expands the role of global coordinator system and controllers of multiple robots system. The global coordinator system creates nocollision trajectories of the virtual leader which is the virtual leader for all vehicles, sub-virtual leaders which are the virtual leader for pertinent followers, and virtual followers. The global coordinator system also implements role assignment algorithm to allocate the role of mobile robots in the formation. The controllers of the individual mobile robots have a task to track the assigned trajectories and also to avoid collision among the mobile robots using the artificial potential field algorithm. The proposed method is tested by experiments of three mobile robots performing leader-follower formation with the shape of a triangle. The experimental results show the robustness of formation of mobile robots even if the leader is manually moved to the arbitrary location, and so that the role of a leader is taken by the nearest mobile robot to the virtual leader.

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